system

Abstract

We provide the system. [Solution] A means for inputting user lifestyle information and housing information, A means for analyzing the input information and automatically generating an optimal cleaning plan, Means for transmitting instructions to a cleaning device based on the generated cleaning plan, A means for monitoring real-time data acquired from the cleaning device and adjusting the cleaning plan as needed, A means of analyzing the condition of the cleaning device and notifying the user of the need for maintenance, A system that includes this.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, the number of dual-income households and busy individuals has been increasing, and the need for vacuum cleaners that can improve and automate house cleaning work within the home has been on the rise. In particular, there is a demand to achieve automated cleaning customized for each user with different living patterns, seamless cooperation with home appliances, and reduce the burden of home management other than cleaning. In such a background, in order to improve convenience, a robot vacuum cleaner system that can flexibly respond according to the user's living habits and the environment of the home is required.

Means for Solving the Problems

[0005] This invention includes means for inputting user lifestyle and housing information, and means for integrating and analyzing this information to automatically generate an optimal cleaning plan. Furthermore, it transmits instructions to the cleaning device based on the generated cleaning plan and controls the operation of the cleaning device. It also has means for monitoring real-time data from the cleaning device and dynamically adjusting the cleaning plan considering the presence or absence of obstacles and power consumption, thereby achieving efficient and effective cleaning. Moreover, it has a function to determine the need for maintenance from the status of the cleaning device and notify the user in a timely manner, thus improving cleaning effectiveness and convenience.

[0006] "User lifestyle information" refers to data about users' daily behavioral patterns and how they spend their time.

[0007] "Residential information" refers to data about the physical space in which a user lives, including information such as the layout of rooms and the arrangement of furniture.

[0008] A "cleaning plan" is a plan that defines the order and timing of cleaning by a robotic vacuum cleaner, optimized based on the user's lifestyle and housing information.

[0009] A "cleaning device" refers to a robotic vacuum cleaner equipped with AI technology that automatically cleans the home.

[0010] The act of "sending instructions" is the process of transmitting action commands to the cleaning equipment based on the generated cleaning plan.

[0011] "Real-time data" refers to information acquired by the cleaning device from sensors and other sources at that moment while cleaning, and includes data such as obstacle detection and battery level.

[0012] "Maintenance needs" refers to the criteria used to determine whether the cleaning device's filters need replacing or its parts need maintenance. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] The AI-equipped cleaning robot system according to this invention is designed to keep the user's living environment cleaner and more comfortable. An embodiment thereof is shown below.

[0035] First, the user accesses the application using their device and inputs information about their lifestyle, the layout of their home, and the arrangement of their furniture. The device then sends this information to the server.

[0036] The server analyzes the user's lifestyle and residence information received and automatically generates a cleaning plan. This plan is then adjusted by generation AI technology to identify the optimal cleaning route and time based on the user's lifestyle.

[0037] The generated cleaning plan is sent from the server to the robotic vacuum cleaner, which is the cleaning device. The robotic vacuum cleaner automatically starts cleaning according to that plan. During cleaning, the vacuum cleaner uses sensors to understand the room's condition in real time and takes actions such as avoiding obstacles.

[0038] Sensor data and status information from the robotic vacuum cleaner during cleaning are constantly monitored by a server. This allows the server to make adjustments based on the power status and the progress of the operation. In particular, the plan is revised when cleaning is about to finish or when battery charging is required.

[0039] Furthermore, the server has a function to determine the maintenance required for long-term use. It appropriately determines when it is time to clean the filter or replace parts, and notifies the user via a terminal. This allows the user to always use the cleaning device in optimal condition.

[0040] As a concrete example, consider a user who has a habit of leaving for work at 7 AM every morning and has registered this information. The server automatically generates a plan so that the robot vacuum cleaner starts cleaning at 8 AM, after the user has left home. In this case, if it is winter, other smart devices could be linked to automatically adjust the heating of the air conditioner, for example.

[0041] In this way, by managing just a small amount of information on a user's daily basis, an efficient and effective cleaning process can be implemented, maintaining comfort within the home.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user uses the device to input personal data such as their daily habits, the layout of their home, and the arrangement of their furniture. The device then prepares to send this information to the server.

[0045] Step 2:

[0046] The server receives user data sent from the terminal. The server analyzes this data and uses it as basic data to identify the user's lifestyle patterns and characteristics of their living environment.

[0047] Step 3:

[0048] The server generates an optimal cleaning plan based on the analyzed data. This plan includes cleaning time, cleaning routes, cleaning frequency, and areas to focus on. It utilizes AI generation technology to create a flexible and adjustable plan.

[0049] Step 4:

[0050] The generated cleaning plan is sent from the server to the robotic vacuum cleaner, which is the cleaning device. The robotic vacuum cleaner prepares to start cleaning based on the plan it received.

[0051] Step 5:

[0052] During cleaning, the robotic vacuum cleaner uses its built-in sensors to detect obstacles and proceeds with cleaning while appropriately avoiding them. It collects real-time data and sends the progress of its operation to the server.

[0053] Step 6:

[0054] The server monitors real-time data received from the robotic vacuum cleaner and dynamically adjusts the cleaning plan if any changes are needed. This includes changing the cleaning path and issuing instructions to pause and resume cleaning.

[0055] Step 7:

[0056] The server analyzes the status data of the cleaning device at regular intervals to determine when filter replacement or parts maintenance is necessary. If necessary, the server sends a notification to the user and advises on the required actions.

[0057] Step 8:

[0058] Users receive notifications from the server via their devices and arrange for maintenance and consumables as needed. This process ensures that the cleaning system is always operated in an optimized state.

[0059] (Example 1)

[0060] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0061] In modern living environments, many users are busy, making regular cleaning difficult. Furthermore, efficient and proper cleaning requires complex scheduling and equipment maintenance. However, many existing systems have limitations in managing these elements comprehensively, placing a heavy burden on users. In this situation, there is a need for a system that enables the creation of efficient cleaning plans that take users' lifestyles into account, as well as proper equipment maintenance.

[0062] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0063] In this invention, the server includes means for users to input lifestyle information and housing environment information using a terminal, means for analyzing the input information and automatically generating an optimal cleaning plan using generation AI technology, and means for transmitting instructions to cleaning equipment via wireless communication based on the generated cleaning plan. This enables the implementation of an efficient and effective cleaning process tailored to the user's lifestyle and optimal maintenance of cleaning equipment.

[0064] "User" refers to the entity that utilizes a service or system, and can refer to an individual or a group of people, including families.

[0065] A "terminal" refers to an electronic device used by a user to input information or operate a device.

[0066] "Lifestyle information" refers to information that compiles a user's daily activity time, behavioral patterns, and related data.

[0067] "Residential environment information" refers to information about the user's residence, such as the physical layout and furniture arrangement.

[0068] A "server" refers to a computer system that has a central function of receiving information from users, performing data analysis, and sending instructions.

[0069] "Generative AI technology" refers to technologies that utilize artificial intelligence to perform data analysis and generate new information.

[0070] A "cleaning plan" refers to a schedule that includes efficient cleaning start times and routes, generated based on user information.

[0071] "Wireless communication" refers to technology that transmits and receives data between electronic devices without using cables.

[0072] "Cleaning equipment" refers to automatically operating devices designed to clean a specific space.

[0073] The system according to this invention is designed to manage the user's life more efficiently and provide a comfortable cleaning environment.

[0074] First, the user launches a dedicated application using their device. This app, known as the "Cleaning Management App," is available for iOS and Android®. Through the app, the user inputs information about their daily routine (e.g., leaving for work at 7 AM every morning) and their living environment (e.g., room layout and furniture arrangement). This information is appropriately formatted on the device and sent to the server in JSON format or similar.

[0075] The server uses a generative AI model in the process of analyzing the received data. Generally, "generative AI technology" is used as the core technology. Specifically, deep learning models are used in information analysis and the creation of optimized cleaning plans. This automatically generates cleaning start times and optimal route plans that are tailored to the user's lifestyle.

[0076] The generated cleaning plan is transmitted wirelessly from the server to the cleaning equipment. The Wi-Fi protocol is used for this communication. The cleaning equipment is an autonomously operating robotic vacuum cleaner that uses built-in LIDAR and ultrasonic sensors to understand its surroundings in real time while operating.

[0077] For example, if a user registers that they "leave for work at 7 AM every morning," the server will generate a cleaning plan that starts cleaning at 8 AM, after the user has left home. This process can also be synchronized with smart devices to adjust the environment within the home.

[0078] In this system, the server monitors sensor data during cleaning and adjusts the plan as needed. Furthermore, based on long-term usage data, it supports proper maintenance by notifying the user when it is time to clean the filter or replace parts. This notification is delivered via push notifications and email through the device.

[0079] An example of a prompt message would be, "Generate a cleaning plan based on the user's cleaning habits. Input data: daily arrival at 7:00 AM, room layout information, furniture arrangement information." This is how instructions are given to the AI ​​model for generating cleaning. In this way, a comfortable cleaning process can be achieved with minimal user input.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The user launches the cleaning management app using their device. Through the app's interface, they input lifestyle information (e.g., work start time) and home environment information (e.g., floor plan, furniture arrangement). This input data is formatted in JSON format. The device then sends this data to the server.

[0083] Step 2:

[0084] After receiving data from the user, the server begins the information analysis process. In this process, a generative AI model is used, taking the received JSON data as input to generate an optimal cleaning plan. This data analysis utilizes machine learning algorithms, and the server calculates the optimal cleaning route and timing, taking into account the user's lifestyle patterns and the layout of the house. As a result of this calculation, a cleaning schedule and route information are output.

[0085] Step 3:

[0086] The generated cleaning plan is transmitted from the server to the cleaning equipment via wireless communication. The communication protocol used here is Wi-Fi. The transmitted data includes the cleaning start time, route information, and various settings. The cleaning equipment prepares to start operating based on the received plan.

[0087] Step 4:

[0088] Once cleaning begins, the cleaning equipment uses built-in LIDAR and ultrasonic sensors to scan its surroundings. This allows it to perform real-time mapping of the room and autonomously avoid obstacles. The cleaning equipment also transmits progress data, battery status, and other information to a server.

[0089] Step 5:

[0090] During and after cleaning, the server monitors sensor data and progress transmitted from the cleaning equipment. It also has the ability to dynamically adjust the cleaning plan as needed. For example, if the battery level is low, the server sends an instruction to the cleaning equipment to return to the charging station. As a result of this adjustment process, cleaning is performed in real time, adapted to the environmental conditions.

[0091] Step 6:

[0092] After the overall cleaning is complete, the server analyzes long-term usage data of the cleaning equipment. This identifies when filters need cleaning and when parts need replacing, and the server notifies the user of this information. Notifications are sent via push notifications on the device or by email, enabling the user to perform appropriate maintenance.

[0093] (Application Example 1)

[0094] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0095] Modern factories are required to maximize production efficiency. However, the complex layout of production lines and machinery presents challenges in developing and implementing efficient cleaning plans. Furthermore, managing the maintenance and upkeep of cleaning equipment to ensure optimal performance over the long term presents challenges. To address these challenges, an automated and efficient cleaning system is necessary.

[0096] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0097] In this invention, the server includes means for acquiring information about the user's life or work, means for analyzing the acquired information and automatically generating an optimal work plan, and means for transmitting instructions to an automated device based on the generated work plan. This enables efficient cleaning work while optimizing productivity within the factory.

[0098] "Information about the user's life or work" refers to detailed data related to the user's lifestyle and work, particularly daily activities and schedules in factories and homes.

[0099] "Means for automatically generating optimal work plans" refers to a function that automatically creates a plan for efficient and effective work based on collected information, using artificial intelligence or algorithms.

[0100] "Means of transmitting instructions to automated devices" refers to communication methods that convey specific work instructions to machines such as robotic vacuum cleaners and robots based on the generated plan.

[0101] "Real-time data" refers to the latest status information provided during operation, meaning data that allows for immediate understanding of equipment status and environmental changes.

[0102] "Means of notifying users of the need for maintenance" refers to a function that determines when machine parts are deteriorating or when maintenance is needed, and informs users of the appropriate time for repair or replacement.

[0103] "Factory layout information and machine operation schedule" refers collectively to information regarding the internal layout of the factory and schedule information indicating when and how the machines are operating.

[0104] To realize this invention, it is necessary to build an AI-powered automated cleaning system that supports efficient cleaning of factories. This system consists of a management terminal, a server, and an automated cleaning device.

[0105] First, users use a management terminal to input factory layout, machine operating schedules, and other relevant data. This data is then transmitted to the server via wireless or wired connection.

[0106] The server uses a generative AI model to analyze the received information. Specifically, it automatically generates an optimal work plan based on the input information and sets efficient cleaning routes and timings using AI technology. This plan is sent to the automated cleaning equipment via the MQTT protocol.

[0107] The cleaning system uses built-in sensors to monitor the factory environment in real time, enabling efficient cleaning. Data acquired from the sensors is fed back to a server using real-time data processing technologies such as Apache® Kafka. The server uses this information to modify the cleaning plan and adjust the system's operating status as needed.

[0108] Furthermore, the server monitors the performance of automated equipment over the long term, predicting, for example, when filters need cleaning or parts need replacing, and appropriately notifying users of the need for maintenance.

[0109] For example, if a factory operates 24 hours a day, the server can track downtime in the production line and generate efficient cleaning routes for those periods. An example of a prompt to input into the AI ​​model is: "Based on the factory layout, production machine placement, and operating schedule, please suggest the optimal cleaning route and start time." This makes it possible to maintain productivity and cleanliness within the factory.

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] Users use a management terminal to input the factory layout and machine operating schedules. This generates the basic data necessary for the work. The entered information is then sent from the terminal to the server.

[0113] Step 2:

[0114] The server begins analysis using a generating AI model based on the received information. Specifically, it analyzes and optimizes the given data to generate efficient cleaning routes and cleaning times within the factory. This results in the output of an optimal work plan.

[0115] Step 3:

[0116] The generated work plan is sent from the server to the automated cleaning device via the MQTT protocol. The cleaning device then starts work according to this plan at pre-set times.

[0117] Step 4:

[0118] While the cleaning equipment is working, it collects data in real time using its onboard sensors. The server receives this data via Apache Kafka and monitors the equipment's operating status and the surrounding environment. This enables real-time situational awareness.

[0119] Step 5:

[0120] The server modifies the cleaning plan as needed based on the monitoring results. For example, it outputs newly optimized instructions based on the detection of obstacles or the degree of cleaning completion, and sends them back to the cleaning equipment.

[0121] Step 6:

[0122] The server analyzes a series of operational records, including past data, to predict when filters need cleaning and when parts need replacing. Based on this, it notifies the user if maintenance is required. This ensures the long-term efficiency of the cleaning equipment.

[0123] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0124] The present invention is an AI-powered cleaning robot system that recognizes user emotions and incorporates them into the cleaning process to provide a more personalized cleaning experience. Embodiments thereof are described below.

[0125] First, the user accesses the application using their device and inputs information about their lifestyle, the layout of their home, and the arrangement of their furniture. In addition, the device uses its camera and voice input to record the user's facial expressions and tone of voice so that the emotion engine can understand the user's daily emotional state. This information is then sent from the device to the server.

[0126] The server analyzes the received user data and emotional information, and automatically generates the optimal cleaning plan according to the user's current mood. For example, if the user wants to relax, the robot vacuum cleaner's operating noise can be reduced and switched to a quiet mode. Conversely, if the user is in an energetic mood, the cleaning speed can be increased and the settings adjusted to efficiently and quickly clean the entire room.

[0127] The cleaning plan generated in this way is sent from the server to the robotic vacuum cleaner. The robotic vacuum cleaner starts cleaning according to the plan and feeds back the collected data to the server in real time. Based on this data, the server further fine-tunes the plan and flexibly responds to changes in the user's emotions.

[0128] Furthermore, the server can coordinate with other home appliances to create an appropriate home environment during cleaning. For example, if the emotion engine determines that the user is feeling down, it can slightly brighten the lighting and adjust it to a warmer color tone. This makes the entire home a more comfortable space and allows the system to better support the user's emotions.

[0129] For example, if the emotion engine identifies that a user is experiencing stress, the server will adjust the scheduled cleaning time to select a time when the user can relax. This can involve various actions, such as playing relaxation music or activating an aroma diffuser.

[0130] As described above, the present invention enables a cleaning experience linked to the user's emotions, thereby providing a better living environment.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] The user uses a device to input information about their lifestyle, living arrangements, and furniture placement. The device uses a camera and microphone for the emotion engine to collect emotional information from the user's facial expressions and voice characteristics. All of this data is sent to a server.

[0134] Step 2:

[0135] The server analyzes the data it receives. It uses lifestyle and housing information to understand the user's typical activity patterns, and analyzes emotional information to identify the user's current emotional state.

[0136] Step 3:

[0137] The server generates an optimal cleaning plan based on the analysis results. This includes setting cleaning modes, times, and routes that take the user's feelings into consideration. For example, if it is determined that the user wants to relax, it will select a cleaning setting that operates quietly.

[0138] Step 4:

[0139] The generated cleaning plan is sent from the server to the robotic vacuum cleaner. The vacuum cleaner starts and executes the cleaning according to the received plan. The noise level and speed during cleaning are maintained to match the user's pre-set emotional state.

[0140] Step 5:

[0141] While cleaning is in progress, the robotic vacuum cleaner sends real-time information about its operating status and obstacles to a server. The server evaluates this real-time data and adjusts the cleaning plan as needed.

[0142] Step 6:

[0143] The server further integrates with other smart home appliances to create a home environment that suits the user's emotions. For example, if it determines that the user is feeling down, it will adjust the room lighting to a comfortable level and play calming music to soothe the user.

[0144] Step 7:

[0145] After cleaning is complete, the server checks the status of the cleaning device and determines whether maintenance is required. If necessary, the server sends a notification to the user via the terminal to prompt appropriate action.

[0146] Step 8:

[0147] Users can check notifications from the server via their terminals and perform maintenance on cleaning equipment or adjust environmental settings as needed. This entire process allows users to maintain a comfortable and efficient living environment at all times.

[0148] (Example 2)

[0149] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0150] Traditional cleaning systems often implemented uniform cleaning plans without considering users' feelings or lifestyles. This made it difficult to provide an environment that was sensitive to users' needs, resulting in the challenge of not being able to maintain a completely comfortable space for them.

[0151] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0152] In this invention, the server includes means for inputting user lifestyle information and living space information, means for generating an optimal cleaning plan by analyzing the user's emotional data, and means for transmitting instructions to cleaning equipment using a generated AI model. This makes it possible to provide personalized cleaning that is tailored to the user's emotions and a comfortable home environment.

[0153] "User lifestyle information" refers to data related to daily activities and specific situations, including information about the user's regular actions and habits.

[0154] "Living space information" refers to information about the physical environment within a house, such as infrastructure, floor plan, and furniture arrangement.

[0155] "Emotional data" refers to data that quantifies a user's mental state, mood, and emotional tendencies, and is information analyzed from facial expressions and tone of voice.

[0156] A "cleaning plan" refers to a set of instructions that include specific schedules, routes, and modes of cleaning for living spaces.

[0157] A "generative AI model" is a type of intelligent system that uses machine learning to analyze data and generate new insights and action plans.

[0158] "Cleaning equipment" refers to mechanical devices designed to perform cleaning tasks automatically and efficiently, and is usually in the form of robots.

[0159] "Household appliances" refers to various electrical appliances and equipment used in the home, including lighting, sound systems, and air conditioning equipment.

[0160] "Household environment conditions" refers to the state of physical or sensory environmental conditions within the home, including the adjustment of temperature, sound, and light.

[0161] This invention is a system that provides an advanced cleaning experience that reflects the user's emotional information, and is implemented using the following technical means.

[0162] Users first access a dedicated application via their device and input personal information and living space details. This information is entered using forms on the device, ensuring privacy while collecting highly accurate data. The devices used in this system include smartphones and tablets.

[0163] Furthermore, the device is equipped with a camera and microphone to collect user emotional data. The camera uses facial expression analysis software to analyze the user's facial expressions in real time, and the microphone performs voice data analysis. As a result, the emotional state is quantified and transmitted to a server.

[0164] The server uses a generative AI model to create a cleaning plan based on the received data. The AI ​​model features advanced algorithms that generate an optimized cleaning plan based on the user's emotions and lifestyle information, specifically including switching cleaning modes and setting schedules. This cleaning plan is then transmitted wirelessly to the cleaning device, which in this case refers to a robotic vacuum cleaner.

[0165] Furthermore, the server can interact with other home devices, optimizing the home environment to match the user's mood. This integration enables control of lighting and sound systems, providing a comfortable environment tailored to the user.

[0166] For example, if a user is feeling stressed, the server can select and play relaxing music from a playlist and adjust the lighting to a softer setting. This provides a comprehensive level of comfort that goes beyond mere cleaning, including relaxation.

[0167] An example of a prompt to input into the generating AI model might be, "Create instructions on how the cleaning robot should behave when the user wants to relax."

[0168] This invention aims to provide a better living space by enabling cleaning and environmental optimization tailored to the individual emotional state of the user.

[0169] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0170] Step 1:

[0171] Users access the application using their devices and input lifestyle and living space information. This input data, including information about the user's lifestyle and furniture arrangement, is used as foundational data in subsequent processes. Specifically, users provide data through an input form and save it to their devices by pressing the submit button.

[0172] Step 2:

[0173] The device uses a camera and microphone to collect user emotion data. This includes facial expression analysis and voice tone recording. Input is the user's real-time facial expressions and voice tone, and output is stored in a database as analyzed emotional states. Image recognition software and voice analysis algorithms are used for the analysis.

[0174] Step 3:

[0175] The device transmits collected lifestyle information and emotional data to the server. The input consists of various data stored on the device, while the output is encrypted transmission data using a security protocol. This allows the server to receive the data securely.

[0176] Step 4:

[0177] The server analyzes the received data and creates a cleaning plan using a generative AI model. The input consists of lifestyle information and emotional data, and the output is an optimized cleaning plan tailored to the user's situation. This plan includes the timing of cleaning commencement and the operating mode. Advanced machine learning algorithms are used for data analysis.

[0178] Step 5:

[0179] The server transmits the generated cleaning plan to the robotic cleaning device via wireless communication. The input is specific instructions based on the cleaning plan, and the output is command data for the cleaning device. This causes the cleaning device to begin operating according to the predetermined plan.

[0180] Step 6:

[0181] The robotic cleaning equipment performs cleaning according to the instructions it receives and feeds back the data collected during the operation to the server. The input is sensor information acquired during cleaning, and the output is real-time data sent to the server. The server dynamically adjusts the cleaning plan based on this data.

[0182] Step 7:

[0183] The server works in conjunction with other household appliances to configure the environment in accordance with the user's emotions. Inputs are environmental parameters to be adjusted (such as lighting brightness and music selection), and outputs are control instructions to the appliances. This optimizes not only the cleaning process but the entire home environment to be sensitive to the user's emotions.

[0184] (Application Example 2)

[0185] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0186] Current cleaning systems operate uniformly without considering the user's emotional state, making it difficult to provide an optimal environment for the user. Furthermore, there is a growing demand for environmental improvements in stores and other spaces that are sensitive to the emotions of visitors. However, current technology does not adequately provide efficient means to achieve this.

[0187] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0188] In this invention, the server includes means for analyzing the user's emotional state and dynamically adjusting the cleaning plan based on that information, means for automatically adjusting the store or space environment settings based on the analyzed user's emotional state, and means for recording the user's facial expressions and tone of voice using a camera and a voice input device. This makes it possible to perform cleaning and environmental adjustments in accordance with the user's emotions.

[0189] "User emotional state" refers to the emotional state of a user, analyzed from their facial expressions, tone of voice, and other factors.

[0190] A "cleaning plan" refers to a set of cleaning procedures and schedules optimized based on the user's emotional state and lifestyle.

[0191] "Environment settings" refers to the state of the surrounding environment, including music, lighting, and other spatial elements.

[0192] "Dynamic adjustment" refers to changing settings and plans in real time according to the situation and conditions.

[0193] "Camera and audio input device" refers to photographic and audio recording equipment used to acquire information on the user's facial expressions and voice.

[0194] A "cloud server" refers to a computer system that stores, calculates, and analyzes data remotely via the internet.

[0195] "Feedback" refers to the process of sending back and analyzing data based on the results and state of the actions performed.

[0196] The system of this invention consists of a user, a server, and a terminal. The user collects their facial expressions and voice using a camera and voice input device mounted on a smartphone or smart glasses. These devices transmit the collected data to a cloud server in real time.

[0197] The server analyzes the user's emotional state based on the received data using a generative AI model. It utilizes machine learning frameworks such as TENSORFLOW® to perform emotion recognition. As a result, it automatically generates an optimal cleaning plan and environmental settings tailored to the user's emotions. The generated plan and settings are then transmitted to the cleaning device and other related appliances for execution.

[0198] For example, if the system determines that the user is relaxed, the server instructs the robot vacuum cleaner to clean in silent mode, simultaneously changes the store lighting to a warm color, and plays calming background music. After the environment is set up, each device feeds its results back to the server, and readjusts are made as needed.

[0199] An example of a prompt message is: "Use a generative AI model to analyze the emotions of customers in the store and suggest the optimal cleaning mode and environmental settings. For example, when customers are relaxing, adjust the music to jazz and the lighting to warm colors."

[0200] This allows for optimal cleaning and environmental adjustments tailored to the user's emotions, providing a more comfortable space.

[0201] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0202] Step 1:

[0203] Users acquire facial and voice information using cameras and voice input devices built into their smartphones or smart glasses. The input consists of facial image data and voice data, which are then used by a generative AI model to analyze emotional states. The data is transmitted to the server in real time.

[0204] Step 2:

[0205] The server processes the received data and uses a facial recognition model and a voice analysis model to analyze the user's emotions. Input is image and audio data from the camera, and output is the user's emotional state (e.g., relaxed, stressed, active, etc.). A machine learning framework (e.g., TensorFlow) is used for the analysis.

[0206] Step 3:

[0207] The server generates a cleaning plan optimized for the user's emotions based on the analyzed emotional state. The input is the analyzed emotional state, and the output is the custom cleaning plan. Specific actions may include instructing the cleaning device to switch to silent mode or high-speed mode.

[0208] Step 4:

[0209] The server sends instructions to relevant home appliances to configure the environment appropriately. The inputs are the analyzed emotional state and associated cleaning plan, and the output is specific appliance operation commands. Examples of specific actions include adjusting the lighting color or playing relaxing music from speakers.

[0210] Step 5:

[0211] The server receives feedback on the results of the instructed cleaning and environmental settings, and uses this information to make further adjustments. Input is feedback information from each device, and output is the updated cleaning plan and environmental settings as needed. Specific examples of its operation include re-evaluating the cleaning area and adjusting the volume.

[0212] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0213] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0214] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0215] [Second Embodiment]

[0216] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0217] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0218] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0219] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0220] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0221] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0222] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0223] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0224] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0225] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0226] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0227] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0228] The AI-equipped cleaning robot system according to this invention is designed to keep the user's living environment cleaner and more comfortable. An embodiment thereof is shown below.

[0229] First, the user accesses the application using their device and inputs information about their lifestyle, the layout of their home, and the arrangement of their furniture. The device then sends this information to the server.

[0230] The server analyzes the user's lifestyle and residence information received and automatically generates a cleaning plan. This plan is then adjusted by generation AI technology to identify the optimal cleaning route and time based on the user's lifestyle.

[0231] The generated cleaning plan is sent from the server to the robotic vacuum cleaner, which is the cleaning device. The robotic vacuum cleaner automatically starts cleaning according to that plan. During cleaning, the vacuum cleaner uses sensors to understand the room's condition in real time and takes actions such as avoiding obstacles.

[0232] Sensor data and status information from the robotic vacuum cleaner during cleaning are constantly monitored by a server. This allows the server to make adjustments based on the power status and the progress of the operation. In particular, the plan is revised when cleaning is about to finish or when battery charging is required.

[0233] Furthermore, the server has a function to determine the maintenance required for long-term use. It appropriately determines when it is time to clean the filter or replace parts, and notifies the user via a terminal. This allows the user to always use the cleaning device in optimal condition.

[0234] As a concrete example, consider a user who has a habit of leaving for work at 7 AM every morning and has registered this information. The server automatically generates a plan so that the robot vacuum cleaner starts cleaning at 8 AM, after the user has left home. In this case, if it is winter, other smart devices could be linked to automatically adjust the heating of the air conditioner, for example.

[0235] In this way, by managing just a small amount of information on a user's daily basis, an efficient and effective cleaning process can be implemented, maintaining comfort within the home.

[0236] The following describes the processing flow.

[0237] Step 1:

[0238] The user uses the device to input personal data such as their daily habits, the layout of their home, and the arrangement of their furniture. The device then prepares to send this information to the server.

[0239] Step 2:

[0240] The server receives user data sent from the terminal. The server analyzes this data and uses it as basic data to identify the user's lifestyle patterns and characteristics of their living environment.

[0241] Step 3:

[0242] The server generates an optimal cleaning plan based on the analyzed data. This plan includes cleaning time, cleaning routes, cleaning frequency, and areas to focus on. It utilizes AI generation technology to create a flexible and adjustable plan.

[0243] Step 4:

[0244] The generated cleaning plan is sent from the server to the robotic vacuum cleaner, which is the cleaning device. The robotic vacuum cleaner prepares to start cleaning based on the plan it received.

[0245] Step 5:

[0246] During cleaning, the robotic vacuum cleaner uses its built-in sensors to detect obstacles and proceeds with cleaning while appropriately avoiding them. It collects real-time data and sends the progress of its operation to the server.

[0247] Step 6:

[0248] The server monitors real-time data received from the robotic vacuum cleaner and dynamically adjusts the cleaning plan if any changes are needed. This includes changing the cleaning path and issuing instructions to pause and resume cleaning.

[0249] Step 7:

[0250] The server analyzes the status data of the cleaning device at regular intervals to determine when filter replacement or parts maintenance is necessary. If necessary, the server sends a notification to the user and advises on the required actions.

[0251] Step 8:

[0252] Users receive notifications from the server via their devices and arrange for maintenance and consumables as needed. This process ensures that the cleaning system is always operated in an optimized state.

[0253] (Example 1)

[0254] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0255] In modern living environments, many users are busy, making regular cleaning difficult. Furthermore, efficient and proper cleaning requires complex scheduling and equipment maintenance. However, many existing systems have limitations in managing these elements comprehensively, placing a heavy burden on users. In this situation, there is a need for a system that enables the creation of efficient cleaning plans that take users' lifestyles into account, as well as proper equipment maintenance.

[0256] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0257] In this invention, the server includes means for users to input lifestyle information and housing environment information using a terminal, means for analyzing the input information and automatically generating an optimal cleaning plan using generation AI technology, and means for transmitting instructions to cleaning equipment via wireless communication based on the generated cleaning plan. This enables the implementation of an efficient and effective cleaning process tailored to the user's lifestyle and optimal maintenance of cleaning equipment.

[0258] "User" refers to the entity that utilizes a service or system, and can refer to an individual or a group of people, including families.

[0259] A "terminal" refers to an electronic device used by a user to input information or operate a device.

[0260] "Lifestyle information" refers to information that compiles a user's daily activity time, behavioral patterns, and related data.

[0261] "Residential environment information" refers to information about the user's residence, such as the physical layout and furniture arrangement.

[0262] A "server" refers to a computer system that has a central function of receiving information from users, performing data analysis, and sending instructions.

[0263] "Generative AI technology" refers to technologies that utilize artificial intelligence to perform data analysis and generate new information.

[0264] A "cleaning plan" refers to a schedule that includes efficient cleaning start times and routes, generated based on user information.

[0265] "Wireless communication" refers to technology that transmits and receives data between electronic devices without using cables.

[0266] "Cleaning equipment" refers to automatically operating devices designed to clean a specific space.

[0267] The system according to this invention is designed to manage the user's life more efficiently and provide a comfortable cleaning environment.

[0268] First, the user launches a dedicated application using their device. This app, called the "Cleaning Management App," is available for both iOS and Android. Through the app, the user inputs information about their daily routine (e.g., leaving for work at 7 AM every morning) and their living environment (e.g., room layout and furniture arrangement). This information is appropriately formatted on the device and sent to the server in JSON format or similar.

[0269] The server uses a generative AI model in the process of analyzing the received data. Generally, "generative AI technology" is used as the core technology. Specifically, deep learning models are used in information analysis and the creation of optimized cleaning plans. This automatically generates cleaning start times and optimal route plans that are tailored to the user's lifestyle.

[0270] The generated cleaning plan is transmitted wirelessly from the server to the cleaning equipment. The Wi-Fi protocol is used for this communication. The cleaning equipment is an autonomously operating robotic vacuum cleaner that uses built-in LIDAR and ultrasonic sensors to understand its surroundings in real time while operating.

[0271] For example, if a user registers that they "leave for work at 7 AM every morning," the server will generate a cleaning plan that starts cleaning at 8 AM, after the user has left home. This process can also be synchronized with smart devices to adjust the environment within the home.

[0272] In this system, the server monitors sensor data during cleaning and adjusts the plan as needed. Furthermore, based on long-term usage data, it supports proper maintenance by notifying the user when it is time to clean the filter or replace parts. This notification is delivered via push notifications and email through the device.

[0273] An example of a prompt message would be, "Generate a cleaning plan based on the user's cleaning habits. Input data: daily arrival at 7:00 AM, room layout information, furniture arrangement information." This is how instructions are given to the AI ​​model for generating cleaning. In this way, a comfortable cleaning process can be achieved with minimal user input.

[0274] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0275] Step 1:

[0276] The user launches the cleaning management app using their device. Through the app's interface, they input lifestyle information (e.g., work start time) and home environment information (e.g., floor plan, furniture arrangement). This input data is formatted in JSON format. The device then sends this data to the server.

[0277] Step 2:

[0278] After receiving data from the user, the server begins the information analysis process. In this process, a generative AI model is used, taking the received JSON data as input to generate an optimal cleaning plan. This data analysis utilizes machine learning algorithms, and the server calculates the optimal cleaning route and timing, taking into account the user's lifestyle patterns and the layout of the house. As a result of this calculation, a cleaning schedule and route information are output.

[0279] Step 3:

[0280] The generated cleaning plan is transmitted from the server to the cleaning equipment via wireless communication. The communication protocol used here is Wi-Fi. The transmitted data includes the cleaning start time, route information, and various settings. The cleaning equipment prepares to start operating based on the received plan.

[0281] Step 4:

[0282] When cleaning starts, the cleaning device uses built-in LIDAR sensors and ultrasonic sensors to scan the surrounding environment. This enables real-time mapping of the room and autonomous operation to avoid obstacles. Additionally, the cleaning device sends progress data, battery status, etc. to the server.

[0283] Step 5:

[0284] During and after cleaning, the server monitors the sensor data and progress sent from the cleaning device. It also has the function to dynamically adjust the cleaning plan as needed. For example, when the remaining battery level drops, the server sends an instruction to the cleaning device to return to the charging station. As a result of this adjustment process, cleaning is executed in real-time according to the adapted environmental conditions.

[0285] Step 6:

[0286] After the overall cleaning is completed, the server analyzes the long-term usage data of the cleaning device. This identifies the filter cleaning time and part replacement time, and the server notifies the user of this information. The notification is sent via push notification or email through the terminal, enabling the user to perform appropriate maintenance.

[0287] (Application Example 1)

[0288] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0289] In modern factories, it is required to maximize production efficiency. However, due to the complex layout of production lines and machinery, there are challenges in formulating and implementing an efficient cleaning plan. There are also challenges in the maintenance and management to keep the cleaning device in an optimal state in the long term. To solve these problems, an automated and efficient cleaning system is necessary.

[0290] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0291] In this invention, the server includes means for acquiring information about the user's life or work, means for analyzing the acquired information and automatically generating an optimal work plan, and means for transmitting instructions to an automated device based on the generated work plan. This enables efficient cleaning work while optimizing productivity within the factory.

[0292] "Information about the user's life or work" refers to detailed data related to the user's lifestyle and work, particularly daily activities and schedules in factories and homes.

[0293] "Means for automatically generating optimal work plans" refers to a function that automatically creates a plan for efficient and effective work based on collected information, using artificial intelligence or algorithms.

[0294] "Means of transmitting instructions to automated devices" refers to communication methods that convey specific work instructions to machines such as robotic vacuum cleaners and robots based on the generated plan.

[0295] "Real-time data" refers to the latest status information provided during operation, meaning data that allows for immediate understanding of equipment status and environmental changes.

[0296] "Means of notifying users of the need for maintenance" refers to a function that determines when machine parts are deteriorating or when maintenance is needed, and informs users of the appropriate time for repair or replacement.

[0297] "Factory layout information and machine operation schedule" refers collectively to information regarding the internal layout of the factory and schedule information indicating when and how the machines are operating.

[0298] To realize this invention, it is necessary to build an AI-powered automated cleaning system that supports efficient cleaning of factories. This system consists of a management terminal, a server, and an automated cleaning device.

[0299] First, users use a management terminal to input factory layout, machine operating schedules, and other relevant data. This data is then transmitted to the server via wireless or wired connection.

[0300] The server uses a generative AI model to analyze the received information. Specifically, it automatically generates an optimal work plan based on the input information and sets efficient cleaning routes and timings using AI technology. This plan is sent to the automated cleaning equipment via the MQTT protocol.

[0301] The cleaning system uses built-in sensors to monitor the factory environment in real time, enabling efficient cleaning. Data acquired from the sensors is fed back to a server using real-time data processing technologies such as Apache Kafka. The server uses this information to modify the cleaning plan and adjust the system's operating status as needed.

[0302] Furthermore, the server monitors the performance of automated equipment over the long term, predicting, for example, when filters need cleaning or parts need replacing, and appropriately notifying users of the need for maintenance.

[0303] For example, if a factory operates 24 hours a day, the server can track downtime in the production line and generate efficient cleaning routes for those periods. An example of a prompt to input into the AI ​​model is: "Based on the factory layout, production machine placement, and operating schedule, please suggest the optimal cleaning route and start time." This makes it possible to maintain productivity and cleanliness within the factory.

[0304] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0305] Step 1:

[0306] The user uses the management terminal to input the layout inside the factory and the operation schedule of the machines. As a result, the basic data required for the work is generated. The input information is sent from the terminal to the server.

[0307] Step 2:

[0308] The server starts the analysis using the generated AI model based on the received information. Specifically, in order to generate an efficient cleaning route and cleaning time inside the factory, the given data is analyzed and optimized. As a result, an optimal work plan is output.

[0309] Step 3:

[0310] The generated work plan is sent from the server to the automated cleaning device via the MQTT protocol. The cleaning device starts working at the preset timing according to this plan.

[0311] Step 4:

[0312] The cleaning device uses the installed sensors to collect data in real time during operation. The server receives this data via Apache Kafka and monitors the operating status of the device and the surrounding environment. As a result, it becomes possible to grasp the real-time situation.

[0313] Step 5:

[0314] The server modifies the cleaning plan as necessary based on the monitoring results. For example, according to the discovery of obstacles or the degree of completion of cleaning, newly optimized instructions are output and sent to the cleaning device again.

[0315] Step 6:

[0316] The server analyzes a series of operational records, including past data, to predict when filters need cleaning and when parts need replacing. Based on this, it notifies the user if maintenance is required. This ensures the long-term efficiency of the cleaning equipment.

[0317] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0318] The present invention is an AI-powered cleaning robot system that recognizes user emotions and incorporates them into the cleaning process to provide a more personalized cleaning experience. Embodiments thereof are described below.

[0319] First, the user accesses the application using their device and inputs information about their lifestyle, the layout of their home, and the arrangement of their furniture. In addition, the device uses its camera and voice input to record the user's facial expressions and tone of voice so that the emotion engine can understand the user's daily emotional state. This information is then sent from the device to the server.

[0320] The server analyzes the received user data and emotional information, and automatically generates the optimal cleaning plan according to the user's current mood. For example, if the user wants to relax, the robot vacuum cleaner's operating noise can be reduced and switched to a quiet mode. Conversely, if the user is in an energetic mood, the cleaning speed can be increased and the settings adjusted to efficiently and quickly clean the entire room.

[0321] The cleaning plan generated in this way is sent from the server to the robotic vacuum cleaner. The robotic vacuum cleaner starts cleaning according to the plan and feeds back the collected data to the server in real time. Based on this data, the server further fine-tunes the plan and flexibly responds to changes in the user's emotions.

[0322] Furthermore, the server can coordinate with other home appliances to create an appropriate home environment during cleaning. For example, if the emotion engine determines that the user is feeling down, it can slightly brighten the lighting and adjust it to a warmer color tone. This makes the entire home a more comfortable space and allows the system to better support the user's emotions.

[0323] For example, if the emotion engine identifies that a user is experiencing stress, the server will adjust the scheduled cleaning time to select a time when the user can relax. This can involve various actions, such as playing relaxation music or activating an aroma diffuser.

[0324] As described above, the present invention enables a cleaning experience linked to the user's emotions, thereby providing a better living environment.

[0325] The following describes the processing flow.

[0326] Step 1:

[0327] The user uses a device to input information about their lifestyle, living arrangements, and furniture placement. The device uses a camera and microphone for the emotion engine to collect emotional information from the user's facial expressions and voice characteristics. All of this data is sent to a server.

[0328] Step 2:

[0329] The server analyzes the data it receives. It uses lifestyle and housing information to understand the user's typical activity patterns, and analyzes emotional information to identify the user's current emotional state.

[0330] Step 3:

[0331] The server generates an optimal cleaning plan based on the analysis results. This includes setting cleaning modes, times, and routes that take the user's feelings into consideration. For example, if it is determined that the user wants to relax, it will select a cleaning setting that operates quietly.

[0332] Step 4:

[0333] The generated cleaning plan is sent from the server to the robotic vacuum cleaner. The vacuum cleaner starts and executes the cleaning according to the received plan. The noise level and speed during cleaning are maintained to match the user's pre-set emotional state.

[0334] Step 5:

[0335] While cleaning is in progress, the robotic vacuum cleaner sends real-time information about its operating status and obstacles to a server. The server evaluates this real-time data and adjusts the cleaning plan as needed.

[0336] Step 6:

[0337] The server further integrates with other smart home appliances to create a home environment that suits the user's emotions. For example, if it determines that the user is feeling down, it will adjust the room lighting to a comfortable level and play calming music to soothe the user.

[0338] Step 7:

[0339] After cleaning is complete, the server checks the status of the cleaning device and determines whether maintenance is required. If necessary, the server sends a notification to the user via the terminal to prompt appropriate action.

[0340] Step 8:

[0341] Users can check notifications from the server via their terminals and perform maintenance on cleaning equipment or adjust environmental settings as needed. This entire process allows users to maintain a comfortable and efficient living environment at all times.

[0342] (Example 2)

[0343] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0344] Traditional cleaning systems often implemented uniform cleaning plans without considering users' feelings or lifestyles. This made it difficult to provide an environment that was sensitive to users' needs, resulting in the challenge of not being able to maintain a completely comfortable space for them.

[0345] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0346] In this invention, the server includes means for inputting user lifestyle information and living space information, means for generating an optimal cleaning plan by analyzing the user's emotional data, and means for transmitting instructions to cleaning equipment using a generated AI model. This makes it possible to provide personalized cleaning that is tailored to the user's emotions and a comfortable home environment.

[0347] "User lifestyle information" refers to data related to daily activities and specific situations, including information about the user's regular actions and habits.

[0348] "Living space information" refers to information about the physical environment within a house, such as infrastructure, floor plan, and furniture arrangement.

[0349] "Emotional data" refers to data that quantifies a user's mental state, mood, and emotional tendencies, and is information analyzed from facial expressions and tone of voice.

[0350] A "cleaning plan" refers to a set of instructions that include specific schedules, routes, and modes of cleaning for living spaces.

[0351] A "generative AI model" is a type of intelligent system that uses machine learning to analyze data and generate new insights and action plans.

[0352] "Cleaning equipment" refers to mechanical devices designed to perform cleaning tasks automatically and efficiently, and is usually in the form of robots.

[0353] "Household appliances" refers to various electrical appliances and equipment used in the home, including lighting, sound systems, and air conditioning equipment.

[0354] "Household environment conditions" refers to the state of physical or sensory environmental conditions within the home, including the adjustment of temperature, sound, and light.

[0355] This invention is a system that provides an advanced cleaning experience that reflects the user's emotional information, and is implemented using the following technical means.

[0356] Users first access a dedicated application via their device and input personal information and living space details. This information is entered using forms on the device, ensuring privacy while collecting highly accurate data. The devices used in this system include smartphones and tablets.

[0357] Furthermore, the device is equipped with a camera and microphone to collect user emotional data. The camera uses facial expression analysis software to analyze the user's facial expressions in real time, and the microphone performs voice data analysis. As a result, the emotional state is quantified and transmitted to a server.

[0358] The server uses a generative AI model to create a cleaning plan based on the received data. The AI ​​model features advanced algorithms that generate an optimized cleaning plan based on the user's emotions and lifestyle information, specifically including switching cleaning modes and setting schedules. This cleaning plan is then transmitted wirelessly to the cleaning device, which in this case refers to a robotic vacuum cleaner.

[0359] Furthermore, the server can interact with other home devices, optimizing the home environment to match the user's mood. This integration enables control of lighting and sound systems, providing a comfortable environment tailored to the user.

[0360] For example, if a user is feeling stressed, the server can select and play relaxing music from a playlist and adjust the lighting to a softer setting. This provides a comprehensive level of comfort that goes beyond mere cleaning, including relaxation.

[0361] An example of a prompt to input into the generating AI model might be, "Create instructions on how the cleaning robot should behave when the user wants to relax."

[0362] This invention aims to provide a better living space by enabling cleaning and environmental optimization tailored to the individual emotional state of the user.

[0363] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0364] Step 1:

[0365] Users access the application using their devices and input lifestyle and living space information. This input data, including information about the user's lifestyle and furniture arrangement, is used as foundational data in subsequent processes. Specifically, users provide data through an input form and save it to their devices by pressing the submit button.

[0366] Step 2:

[0367] The device uses a camera and microphone to collect user emotion data. This includes facial expression analysis and voice tone recording. Input is the user's real-time facial expressions and voice tone, and output is stored in a database as analyzed emotional states. Image recognition software and voice analysis algorithms are used for the analysis.

[0368] Step 3:

[0369] The device transmits collected lifestyle information and emotional data to the server. The input consists of various data stored on the device, while the output is encrypted transmission data using a security protocol. This allows the server to receive the data securely.

[0370] Step 4:

[0371] The server analyzes the received data and creates a cleaning plan using a generative AI model. The input consists of lifestyle information and emotional data, and the output is an optimized cleaning plan tailored to the user's situation. This plan includes the timing of cleaning commencement and the operating mode. Advanced machine learning algorithms are used for data analysis.

[0372] Step 5:

[0373] The server transmits the generated cleaning plan to the robotic cleaning device via wireless communication. The input is specific instructions based on the cleaning plan, and the output is command data for the cleaning device. This causes the cleaning device to begin operating according to the predetermined plan.

[0374] Step 6:

[0375] The robotic cleaning equipment performs cleaning according to the instructions it receives and feeds back the data collected during the operation to the server. The input is sensor information acquired during cleaning, and the output is real-time data sent to the server. The server dynamically adjusts the cleaning plan based on this data.

[0376] Step 7:

[0377] The server works in conjunction with other household appliances to configure the environment in accordance with the user's emotions. Inputs are environmental parameters to be adjusted (such as lighting brightness and music selection), and outputs are control instructions to the appliances. This optimizes not only the cleaning process but the entire home environment to be sensitive to the user's emotions.

[0378] (Application Example 2)

[0379] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0380] Current cleaning systems operate uniformly without considering the user's emotional state, making it difficult to provide an optimal environment for the user. Furthermore, there is a growing demand for environmental improvements in stores and other spaces that are sensitive to the emotions of visitors. However, current technology does not adequately provide efficient means to achieve this.

[0381] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0382] In this invention, the server includes means for analyzing the user's emotional state and dynamically adjusting the cleaning plan based on that information, means for automatically adjusting the store or space environment settings based on the analyzed user's emotional state, and means for recording the user's facial expressions and tone of voice using a camera and a voice input device. This makes it possible to perform cleaning and environmental adjustments in accordance with the user's emotions.

[0383] "User emotional state" refers to the emotional state of a user, analyzed from their facial expressions, tone of voice, and other factors.

[0384] A "cleaning plan" refers to a set of cleaning procedures and schedules optimized based on the user's emotional state and lifestyle.

[0385] "Environment settings" refers to the state of the surrounding environment, including music, lighting, and other spatial elements.

[0386] "Dynamic adjustment" refers to changing settings and plans in real time according to the situation and conditions.

[0387] "Camera and audio input device" refers to photographic and audio recording equipment used to acquire information on the user's facial expressions and voice.

[0388] A "cloud server" refers to a computer system that stores, calculates, and analyzes data remotely via the internet.

[0389] "Feedback" refers to the process of sending back and analyzing data based on the results and state of the actions performed.

[0390] The system of this invention consists of a user, a server, and a terminal. The user collects their facial expressions and voice using a camera and voice input device mounted on a smartphone or smart glasses. These devices transmit the collected data to a cloud server in real time.

[0391] The server analyzes the user's emotional state based on the received data using a generative AI model. It utilizes machine learning frameworks such as TensorFlow for emotion recognition. As a result, it automatically generates an optimal cleaning plan and environmental settings tailored to the user's emotions. The generated plan and settings are then transmitted to the cleaning device and other related appliances for execution.

[0392] For example, if the system determines that the user is relaxed, the server instructs the robot vacuum cleaner to clean in silent mode, simultaneously changes the store lighting to a warm color, and plays calming background music. After the environment is set up, each device feeds its results back to the server, and readjusts are made as needed.

[0393] An example of a prompt message is: "Use a generative AI model to analyze the emotions of customers in the store and suggest the optimal cleaning mode and environmental settings. For example, when customers are relaxing, adjust the music to jazz and the lighting to warm colors."

[0394] This allows for optimal cleaning and environmental adjustments tailored to the user's emotions, providing a more comfortable space.

[0395] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0396] Step 1:

[0397] Users acquire facial and voice information using cameras and voice input devices built into their smartphones or smart glasses. The input consists of facial image data and voice data, which are then used by a generative AI model to analyze emotional states. The data is transmitted to the server in real time.

[0398] Step 2:

[0399] The server processes the received data and uses a facial recognition model and a voice analysis model to analyze the user's emotions. Input is image and audio data from the camera, and output is the user's emotional state (e.g., relaxed, stressed, active, etc.). A machine learning framework (e.g., TensorFlow) is used for the analysis.

[0400] Step 3:

[0401] The server generates a cleaning plan optimized for the user's emotions based on the analyzed emotional state. The input is the analyzed emotional state, and the output is the custom cleaning plan. Specific actions may include instructing the cleaning device to switch to silent mode or high-speed mode.

[0402] Step 4:

[0403] The server sends instructions to relevant home appliances to configure the environment appropriately. The inputs are the analyzed emotional state and associated cleaning plan, and the output is specific appliance operation commands. Examples of specific actions include adjusting the lighting color or playing relaxing music from speakers.

[0404] Step 5:

[0405] The server receives feedback on the results of the instructed cleaning and environmental settings, and uses this information to make further adjustments. Input is feedback information from each device, and output is the updated cleaning plan and environmental settings as needed. Specific examples of its operation include re-evaluating the cleaning area and adjusting the volume.

[0406] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0407] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0408] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0409] [Third Embodiment]

[0410] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0411] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0412] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0413] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0414] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0415] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0416] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0417] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0418] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0419] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0420] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0421] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0422] The AI-equipped cleaning robot system according to this invention is designed to keep the user's living environment cleaner and more comfortable. An embodiment thereof is shown below.

[0423] First, the user accesses the application using their device and inputs information about their lifestyle, the layout of their home, and the arrangement of their furniture. The device then sends this information to the server.

[0424] The server analyzes the user's lifestyle and residence information received and automatically generates a cleaning plan. This plan is then adjusted by generation AI technology to identify the optimal cleaning route and time based on the user's lifestyle.

[0425] The generated cleaning plan is sent from the server to the robotic vacuum cleaner, which is the cleaning device. The robotic vacuum cleaner automatically starts cleaning according to that plan. During cleaning, the vacuum cleaner uses sensors to understand the room's condition in real time and takes actions such as avoiding obstacles.

[0426] Sensor data and status information from the robotic vacuum cleaner during cleaning are constantly monitored by a server. This allows the server to make adjustments based on the power status and the progress of the operation. In particular, the plan is revised when cleaning is about to finish or when battery charging is required.

[0427] Furthermore, the server has a function to determine the maintenance required for long-term use. It appropriately determines when it is time to clean the filter or replace parts, and notifies the user via a terminal. This allows the user to always use the cleaning device in optimal condition.

[0428] As a concrete example, consider a user who has a habit of leaving for work at 7 AM every morning and has registered this information. The server automatically generates a plan so that the robot vacuum cleaner starts cleaning at 8 AM, after the user has left home. In this case, if it is winter, other smart devices could be linked to automatically adjust the heating of the air conditioner, for example.

[0429] In this way, by managing just a small amount of information on a user's daily basis, an efficient and effective cleaning process can be implemented, maintaining comfort within the home.

[0430] The following describes the processing flow.

[0431] Step 1:

[0432] The user uses the device to input personal data such as their daily habits, the layout of their home, and the arrangement of their furniture. The device then prepares to send this information to the server.

[0433] Step 2:

[0434] The server receives user data sent from the terminal. The server analyzes this data and uses it as basic data to identify the user's lifestyle patterns and characteristics of their living environment.

[0435] Step 3:

[0436] The server generates an optimal cleaning plan based on the analyzed data. This plan includes cleaning time, cleaning routes, cleaning frequency, and areas to focus on. It utilizes AI generation technology to create a flexible and adjustable plan.

[0437] Step 4:

[0438] The generated cleaning plan is sent from the server to the robotic vacuum cleaner, which is the cleaning device. The robotic vacuum cleaner prepares to start cleaning based on the plan it received.

[0439] Step 5:

[0440] During cleaning, the robotic vacuum cleaner uses its built-in sensors to detect obstacles and proceeds with cleaning while appropriately avoiding them. It collects real-time data and sends the progress of its operation to the server.

[0441] Step 6:

[0442] The server monitors real-time data received from the robotic vacuum cleaner and dynamically adjusts the cleaning plan if any changes are needed. This includes changing the cleaning path and issuing instructions to pause and resume cleaning.

[0443] Step 7:

[0444] The server analyzes the status data of the cleaning device at regular intervals to determine when filter replacement or parts maintenance is necessary. If necessary, the server sends a notification to the user and advises on the required actions.

[0445] Step 8:

[0446] Users receive notifications from the server via their devices and arrange for maintenance and consumables as needed. This process ensures that the cleaning system is always operated in an optimized state.

[0447] (Example 1)

[0448] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0449] In modern living environments, many users are busy, making regular cleaning difficult. Furthermore, efficient and proper cleaning requires complex scheduling and equipment maintenance. However, many existing systems have limitations in managing these elements comprehensively, placing a heavy burden on users. In this situation, there is a need for a system that enables the creation of efficient cleaning plans that take users' lifestyles into account, as well as proper equipment maintenance.

[0450] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0451] In this invention, the server includes means for users to input lifestyle information and housing environment information using a terminal, means for analyzing the input information and automatically generating an optimal cleaning plan using generation AI technology, and means for transmitting instructions to cleaning equipment via wireless communication based on the generated cleaning plan. This enables the implementation of an efficient and effective cleaning process tailored to the user's lifestyle and optimal maintenance of cleaning equipment.

[0452] "User" refers to the entity that utilizes a service or system, and can refer to an individual or a group of people, including families.

[0453] A "terminal" refers to an electronic device used by a user to input information or operate a device.

[0454] "Lifestyle information" refers to information that compiles a user's daily activity time, behavioral patterns, and related data.

[0455] "Residential environment information" refers to information about the user's residence, such as the physical layout and furniture arrangement.

[0456] A "server" refers to a computer system that has a central function of receiving information from users, performing data analysis, and sending instructions.

[0457] "Generative AI technology" refers to technologies that utilize artificial intelligence to perform data analysis and generate new information.

[0458] A "cleaning plan" refers to a schedule that includes efficient cleaning start times and routes, generated based on user information.

[0459] "Wireless communication" refers to technology that transmits and receives data between electronic devices without using cables.

[0460] "Cleaning equipment" refers to automatically operating devices designed to clean a specific space.

[0461] The system according to this invention is designed to manage the user's life more efficiently and provide a comfortable cleaning environment.

[0462] First, the user launches a dedicated application using their device. This app, called the "Cleaning Management App," is available for both iOS and Android. Through the app, the user inputs information about their daily routine (e.g., leaving for work at 7 AM every morning) and their living environment (e.g., room layout and furniture arrangement). This information is appropriately formatted on the device and sent to the server in JSON format or similar.

[0463] The server uses a generative AI model in the process of analyzing the received data. Generally, "generative AI technology" is used as the core technology. Specifically, deep learning models are used in information analysis and the creation of optimized cleaning plans. This automatically generates cleaning start times and optimal route plans that are tailored to the user's lifestyle.

[0464] The generated cleaning plan is transmitted wirelessly from the server to the cleaning equipment. The Wi-Fi protocol is used for this communication. The cleaning equipment is an autonomously operating robotic vacuum cleaner that uses built-in LIDAR and ultrasonic sensors to understand its surroundings in real time while operating.

[0465] For example, if a user registers that they "leave for work at 7 AM every morning," the server will generate a cleaning plan that starts cleaning at 8 AM, after the user has left home. This process can also be synchronized with smart devices to adjust the environment within the home.

[0466] In this system, the server monitors sensor data during cleaning and adjusts the plan as needed. Furthermore, based on long-term usage data, it supports proper maintenance by notifying the user when it is time to clean the filter or replace parts. This notification is delivered via push notifications and email through the device.

[0467] An example of a prompt message would be, "Generate a cleaning plan based on the user's cleaning habits. Input data: daily arrival at 7:00 AM, room layout information, furniture arrangement information." This is how instructions are given to the AI ​​model for generating cleaning. In this way, a comfortable cleaning process can be achieved with minimal user input.

[0468] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0469] Step 1:

[0470] The user launches the cleaning management app using their device. Through the app's interface, they input lifestyle information (e.g., work start time) and home environment information (e.g., floor plan, furniture arrangement). This input data is formatted in JSON format. The device then sends this data to the server.

[0471] Step 2:

[0472] After receiving data from the user, the server begins the information analysis process. In this process, a generative AI model is used, taking the received JSON data as input to generate an optimal cleaning plan. This data analysis utilizes machine learning algorithms, and the server calculates the optimal cleaning route and timing, taking into account the user's lifestyle patterns and the layout of the house. As a result of this calculation, a cleaning schedule and route information are output.

[0473] Step 3:

[0474] The generated cleaning plan is transmitted from the server to the cleaning equipment via wireless communication. The communication protocol used here is Wi-Fi. The transmitted data includes the cleaning start time, route information, and various settings. The cleaning equipment prepares to start operating based on the received plan.

[0475] Step 4:

[0476] Once cleaning begins, the cleaning equipment uses built-in LIDAR and ultrasonic sensors to scan its surroundings. This allows it to perform real-time mapping of the room and autonomously avoid obstacles. The cleaning equipment also transmits progress data, battery status, and other information to a server.

[0477] Step 5:

[0478] During and after cleaning, the server monitors sensor data and progress transmitted from the cleaning equipment. It also has the ability to dynamically adjust the cleaning plan as needed. For example, if the battery level is low, the server sends an instruction to the cleaning equipment to return to the charging station. As a result of this adjustment process, cleaning is performed in real time, adapted to the environmental conditions.

[0479] Step 6:

[0480] After the overall cleaning is complete, the server analyzes long-term usage data of the cleaning equipment. This identifies when filters need cleaning and when parts need replacing, and the server notifies the user of this information. Notifications are sent via push notifications on the device or by email, enabling the user to perform appropriate maintenance.

[0481] (Application Example 1)

[0482] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0483] Modern factories are required to maximize production efficiency. However, the complex layout of production lines and machinery presents challenges in developing and implementing efficient cleaning plans. Furthermore, managing the maintenance and upkeep of cleaning equipment to ensure optimal performance over the long term presents challenges. To address these challenges, an automated and efficient cleaning system is necessary.

[0484] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0485] In this invention, the server includes means for acquiring information about the user's life or work, means for analyzing the acquired information and automatically generating an optimal work plan, and means for transmitting instructions to an automated device based on the generated work plan. This enables efficient cleaning work while optimizing productivity within the factory.

[0486] "Information about the user's life or work" refers to detailed data related to the user's lifestyle and work, particularly daily activities and schedules in factories and homes.

[0487] "Means for automatically generating optimal work plans" refers to a function that automatically creates a plan for efficient and effective work based on collected information, using artificial intelligence or algorithms.

[0488] "Means of transmitting instructions to automated devices" refers to communication methods that convey specific work instructions to machines such as robotic vacuum cleaners and robots based on the generated plan.

[0489] "Real-time data" refers to the latest status information provided during operation, meaning data that allows for immediate understanding of equipment status and environmental changes.

[0490] "Means of notifying users of the need for maintenance" refers to a function that determines when machine parts are deteriorating or when maintenance is needed, and informs users of the appropriate time for repair or replacement.

[0491] "Factory layout information and machine operation schedule" refers collectively to information regarding the internal layout of the factory and schedule information indicating when and how the machines are operating.

[0492] To realize this invention, it is necessary to build an AI-powered automated cleaning system that supports efficient cleaning of factories. This system consists of a management terminal, a server, and an automated cleaning device.

[0493] First, users use a management terminal to input factory layout, machine operating schedules, and other relevant data. This data is then transmitted to the server via wireless or wired connection.

[0494] The server uses a generative AI model to analyze the received information. Specifically, it automatically generates an optimal work plan based on the input information and sets efficient cleaning routes and timings using AI technology. This plan is sent to the automated cleaning equipment via the MQTT protocol.

[0495] The cleaning system uses built-in sensors to monitor the factory environment in real time, enabling efficient cleaning. Data acquired from the sensors is fed back to a server using real-time data processing technologies such as Apache Kafka. The server uses this information to modify the cleaning plan and adjust the system's operating status as needed.

[0496] Furthermore, the server monitors the performance of automated equipment over the long term, predicting, for example, when filters need cleaning or parts need replacing, and appropriately notifying users of the need for maintenance.

[0497] For example, if a factory operates 24 hours a day, the server can track downtime in the production line and generate efficient cleaning routes for those periods. An example of a prompt to input into the AI ​​model is: "Based on the factory layout, production machine placement, and operating schedule, please suggest the optimal cleaning route and start time." This makes it possible to maintain productivity and cleanliness within the factory.

[0498] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0499] Step 1:

[0500] Users use a management terminal to input the factory layout and machine operating schedules. This generates the basic data necessary for the work. The entered information is then sent from the terminal to the server.

[0501] Step 2:

[0502] The server begins analysis using a generating AI model based on the received information. Specifically, it analyzes and optimizes the given data to generate efficient cleaning routes and cleaning times within the factory. This results in the output of an optimal work plan.

[0503] Step 3:

[0504] The generated work plan is sent from the server to the automated cleaning device via the MQTT protocol. The cleaning device then starts work according to this plan at pre-set times.

[0505] Step 4:

[0506] While the cleaning equipment is working, it collects data in real time using its onboard sensors. The server receives this data via Apache Kafka and monitors the equipment's operating status and the surrounding environment. This enables real-time situational awareness.

[0507] Step 5:

[0508] The server modifies the cleaning plan as needed based on the monitoring results. For example, it outputs newly optimized instructions based on the detection of obstacles or the degree of cleaning completion, and sends them back to the cleaning equipment.

[0509] Step 6:

[0510] The server analyzes a series of operational records, including past data, to predict when filters need cleaning and when parts need replacing. Based on this, it notifies the user if maintenance is required. This ensures the long-term efficiency of the cleaning equipment.

[0511] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0512] The present invention is an AI-powered cleaning robot system that recognizes user emotions and incorporates them into the cleaning process to provide a more personalized cleaning experience. Embodiments thereof are described below.

[0513] First, the user accesses the application using their device and inputs information about their lifestyle, the layout of their home, and the arrangement of their furniture. In addition, the device uses its camera and voice input to record the user's facial expressions and tone of voice so that the emotion engine can understand the user's daily emotional state. This information is then sent from the device to the server.

[0514] The server analyzes the received user data and emotional information, and automatically generates the optimal cleaning plan according to the user's current mood. For example, if the user wants to relax, the robot vacuum cleaner's operating noise can be reduced and switched to a quiet mode. Conversely, if the user is in an energetic mood, the cleaning speed can be increased and the settings adjusted to efficiently and quickly clean the entire room.

[0515] The cleaning plan generated in this way is sent from the server to the robotic vacuum cleaner. The robotic vacuum cleaner starts cleaning according to the plan and feeds back the collected data to the server in real time. Based on this data, the server further fine-tunes the plan and flexibly responds to changes in the user's emotions.

[0516] Furthermore, the server can coordinate with other home appliances to create an appropriate home environment during cleaning. For example, if the emotion engine determines that the user is feeling down, it can slightly brighten the lighting and adjust it to a warmer color tone. This makes the entire home a more comfortable space and allows the system to better support the user's emotions.

[0517] For example, if the emotion engine identifies that a user is experiencing stress, the server will adjust the scheduled cleaning time to select a time when the user can relax. This can involve various actions, such as playing relaxation music or activating an aroma diffuser.

[0518] As described above, the present invention enables a cleaning experience linked to the user's emotions, thereby providing a better living environment.

[0519] The following describes the processing flow.

[0520] Step 1:

[0521] The user uses a device to input information about their lifestyle, living arrangements, and furniture placement. The device uses a camera and microphone for the emotion engine to collect emotional information from the user's facial expressions and voice characteristics. All of this data is sent to a server.

[0522] Step 2:

[0523] The server analyzes the data it receives. It uses lifestyle and housing information to understand the user's typical activity patterns, and analyzes emotional information to identify the user's current emotional state.

[0524] Step 3:

[0525] The server generates an optimal cleaning plan based on the analysis results. This includes setting cleaning modes, times, and routes that take the user's feelings into consideration. For example, if it is determined that the user wants to relax, it will select a cleaning setting that operates quietly.

[0526] Step 4:

[0527] The generated cleaning plan is sent from the server to the robotic vacuum cleaner. The vacuum cleaner starts and executes the cleaning according to the received plan. The noise level and speed during cleaning are maintained to match the user's pre-set emotional state.

[0528] Step 5:

[0529] While cleaning is in progress, the robotic vacuum cleaner sends real-time information about its operating status and obstacles to a server. The server evaluates this real-time data and adjusts the cleaning plan as needed.

[0530] Step 6:

[0531] The server further integrates with other smart home appliances to create a home environment that suits the user's emotions. For example, if it determines that the user is feeling down, it will adjust the room lighting to a comfortable level and play calming music to soothe the user.

[0532] Step 7:

[0533] After cleaning is complete, the server checks the status of the cleaning device and determines whether maintenance is required. If necessary, the server sends a notification to the user via the terminal to prompt appropriate action.

[0534] Step 8:

[0535] Users can check notifications from the server via their terminals and perform maintenance on cleaning equipment or adjust environmental settings as needed. This entire process allows users to maintain a comfortable and efficient living environment at all times.

[0536] (Example 2)

[0537] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0538] Traditional cleaning systems often implemented uniform cleaning plans without considering users' feelings or lifestyles. This made it difficult to provide an environment that was sensitive to users' needs, resulting in the challenge of not being able to maintain a completely comfortable space for them.

[0539] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0540] In this invention, the server includes means for inputting user lifestyle information and living space information, means for generating an optimal cleaning plan by analyzing the user's emotional data, and means for transmitting instructions to cleaning equipment using a generated AI model. This makes it possible to provide personalized cleaning that is tailored to the user's emotions and a comfortable home environment.

[0541] "User lifestyle information" refers to data related to daily activities and specific situations, including information about the user's regular actions and habits.

[0542] "Living space information" refers to information about the physical environment within a house, such as infrastructure, floor plan, and furniture arrangement.

[0543] "Emotional data" refers to data that quantifies a user's mental state, mood, and emotional tendencies, and is information analyzed from facial expressions and tone of voice.

[0544] A "cleaning plan" refers to a set of instructions that include specific schedules, routes, and modes of cleaning for living spaces.

[0545] A "generative AI model" is a type of intelligent system that uses machine learning to analyze data and generate new insights and action plans.

[0546] "Cleaning equipment" refers to mechanical devices designed to perform cleaning tasks automatically and efficiently, and is usually in the form of robots.

[0547] "Household appliances" refers to various electrical appliances and equipment used in the home, including lighting, sound systems, and air conditioning equipment.

[0548] "Household environment conditions" refers to the state of physical or sensory environmental conditions within the home, including the adjustment of temperature, sound, and light.

[0549] This invention is a system that provides an advanced cleaning experience that reflects the user's emotional information, and is implemented using the following technical means.

[0550] Users first access a dedicated application via their device and input personal information and living space details. This information is entered using forms on the device, ensuring privacy while collecting highly accurate data. The devices used in this system include smartphones and tablets.

[0551] Furthermore, the device is equipped with a camera and microphone to collect user emotional data. The camera uses facial expression analysis software to analyze the user's facial expressions in real time, and the microphone performs voice data analysis. As a result, the emotional state is quantified and transmitted to a server.

[0552] The server uses a generative AI model to create a cleaning plan based on the received data. The AI ​​model features advanced algorithms that generate an optimized cleaning plan based on the user's emotions and lifestyle information, specifically including switching cleaning modes and setting schedules. This cleaning plan is then transmitted wirelessly to the cleaning device, which in this case refers to a robotic vacuum cleaner.

[0553] Furthermore, the server can interact with other home devices, optimizing the home environment to match the user's mood. This integration enables control of lighting and sound systems, providing a comfortable environment tailored to the user.

[0554] For example, if a user is feeling stressed, the server can select and play relaxing music from a playlist and adjust the lighting to a softer setting. This provides a comprehensive level of comfort that goes beyond mere cleaning, including relaxation.

[0555] An example of a prompt to input into the generating AI model might be, "Create instructions on how the cleaning robot should behave when the user wants to relax."

[0556] This invention aims to provide a better living space by enabling cleaning and environmental optimization tailored to the individual emotional state of the user.

[0557] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0558] Step 1:

[0559] Users access the application using their devices and input lifestyle and living space information. This input data, including information about the user's lifestyle and furniture arrangement, is used as foundational data in subsequent processes. Specifically, users provide data through an input form and save it to their devices by pressing the submit button.

[0560] Step 2:

[0561] The device uses a camera and microphone to collect user emotion data. This includes facial expression analysis and voice tone recording. Input is the user's real-time facial expressions and voice tone, and output is stored in a database as analyzed emotional states. Image recognition software and voice analysis algorithms are used for the analysis.

[0562] Step 3:

[0563] The device transmits collected lifestyle information and emotional data to the server. The input consists of various data stored on the device, while the output is encrypted transmission data using a security protocol. This allows the server to receive the data securely.

[0564] Step 4:

[0565] The server analyzes the received data and creates a cleaning plan using a generative AI model. The input consists of lifestyle information and emotional data, and the output is an optimized cleaning plan tailored to the user's situation. This plan includes the timing of cleaning commencement and the operating mode. Advanced machine learning algorithms are used for data analysis.

[0566] Step 5:

[0567] The server transmits the generated cleaning plan to the robotic cleaning device via wireless communication. The input is specific instructions based on the cleaning plan, and the output is command data for the cleaning device. This causes the cleaning device to begin operating according to the predetermined plan.

[0568] Step 6:

[0569] The robotic cleaning equipment performs cleaning according to the instructions it receives and feeds back the data collected during the operation to the server. The input is sensor information acquired during cleaning, and the output is real-time data sent to the server. The server dynamically adjusts the cleaning plan based on this data.

[0570] Step 7:

[0571] The server works in conjunction with other household appliances to configure the environment in accordance with the user's emotions. Inputs are environmental parameters to be adjusted (such as lighting brightness and music selection), and outputs are control instructions to the appliances. This optimizes not only the cleaning process but the entire home environment to be sensitive to the user's emotions.

[0572] (Application Example 2)

[0573] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0574] Current cleaning systems operate uniformly without considering the user's emotional state, making it difficult to provide an optimal environment for the user. Furthermore, there is a growing demand for environmental improvements in stores and other spaces that are sensitive to the emotions of visitors. However, current technology does not adequately provide efficient means to achieve this.

[0575] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0576] In this invention, the server includes means for analyzing the user's emotional state and dynamically adjusting the cleaning plan based on that information, means for automatically adjusting the store or space environment settings based on the analyzed user's emotional state, and means for recording the user's facial expressions and tone of voice using a camera and a voice input device. This makes it possible to perform cleaning and environmental adjustments in accordance with the user's emotions.

[0577] "User emotional state" refers to the emotional state of a user, analyzed from their facial expressions, tone of voice, and other factors.

[0578] A "cleaning plan" refers to a set of cleaning procedures and schedules optimized based on the user's emotional state and lifestyle.

[0579] "Environment settings" refers to the state of the surrounding environment, including music, lighting, and other spatial elements.

[0580] "Dynamic adjustment" refers to changing settings and plans in real time according to the situation and conditions.

[0581] "Camera and audio input device" refers to photographic and audio recording equipment used to acquire information on the user's facial expressions and voice.

[0582] A "cloud server" refers to a computer system that stores, calculates, and analyzes data remotely via the internet.

[0583] "Feedback" refers to the process of sending back and analyzing data based on the results and state of the actions performed.

[0584] The system of this invention consists of a user, a server, and a terminal. The user collects their facial expressions and voice using a camera and voice input device mounted on a smartphone or smart glasses. These devices transmit the collected data to a cloud server in real time.

[0585] The server analyzes the user's emotional state based on the received data using a generative AI model. It utilizes machine learning frameworks such as TensorFlow for emotion recognition. As a result, it automatically generates an optimal cleaning plan and environmental settings tailored to the user's emotions. The generated plan and settings are then transmitted to the cleaning device and other related appliances for execution.

[0586] For example, if the system determines that the user is relaxed, the server instructs the robot vacuum cleaner to clean in silent mode, simultaneously changes the store lighting to a warm color, and plays calming background music. After the environment is set up, each device feeds its results back to the server, and readjusts are made as needed.

[0587] An example of a prompt message is: "Use a generative AI model to analyze the emotions of customers in the store and suggest the optimal cleaning mode and environmental settings. For example, when customers are relaxing, adjust the music to jazz and the lighting to warm colors."

[0588] This allows for optimal cleaning and environmental adjustments tailored to the user's emotions, providing a more comfortable space.

[0589] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0590] Step 1:

[0591] Users acquire facial and voice information using cameras and voice input devices built into their smartphones or smart glasses. The input consists of facial image data and voice data, which are then used by a generative AI model to analyze emotional states. The data is transmitted to the server in real time.

[0592] Step 2:

[0593] The server processes the received data and uses a facial recognition model and a voice analysis model to analyze the user's emotions. Input is image and audio data from the camera, and output is the user's emotional state (e.g., relaxed, stressed, active, etc.). A machine learning framework (e.g., TensorFlow) is used for the analysis.

[0594] Step 3:

[0595] The server generates a cleaning plan optimized for the user's emotions based on the analyzed emotional state. The input is the analyzed emotional state, and the output is the custom cleaning plan. Specific actions may include instructing the cleaning device to switch to silent mode or high-speed mode.

[0596] Step 4:

[0597] The server sends instructions to relevant home appliances to configure the environment appropriately. The inputs are the analyzed emotional state and associated cleaning plan, and the output is specific appliance operation commands. Examples of specific actions include adjusting the lighting color or playing relaxing music from speakers.

[0598] Step 5:

[0599] The server receives feedback on the results of the instructed cleaning and environmental settings, and uses this information to make further adjustments. Input is feedback information from each device, and output is the updated cleaning plan and environmental settings as needed. Specific examples of its operation include re-evaluating the cleaning area and adjusting the volume.

[0600] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0601] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0602] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0603] [Fourth Embodiment]

[0604] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0605] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0606] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0607] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0608] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0609] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0610] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0611] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0612] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0613] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0614] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0615] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0616] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0617] The AI-equipped cleaning robot system according to this invention is designed to keep the user's living environment cleaner and more comfortable. An embodiment thereof is shown below.

[0618] First, the user accesses the application using their device and inputs information about their lifestyle, the layout of their home, and the arrangement of their furniture. The device then sends this information to the server.

[0619] The server analyzes the user's lifestyle and residence information received and automatically generates a cleaning plan. This plan is then adjusted by generation AI technology to identify the optimal cleaning route and time based on the user's lifestyle.

[0620] The generated cleaning plan is sent from the server to the robotic vacuum cleaner, which is the cleaning device. The robotic vacuum cleaner automatically starts cleaning according to that plan. During cleaning, the vacuum cleaner uses sensors to understand the room's condition in real time and takes actions such as avoiding obstacles.

[0621] Sensor data and status information from the robotic vacuum cleaner during cleaning are constantly monitored by a server. This allows the server to make adjustments based on the power status and the progress of the operation. In particular, the plan is revised when cleaning is about to finish or when battery charging is required.

[0622] Furthermore, the server has a function to determine the maintenance required for long-term use. It appropriately determines when it is time to clean the filter or replace parts, and notifies the user via a terminal. This allows the user to always use the cleaning device in optimal condition.

[0623] As a concrete example, consider a user who has a habit of leaving for work at 7 AM every morning and has registered this information. The server automatically generates a plan so that the robot vacuum cleaner starts cleaning at 8 AM, after the user has left home. In this case, if it is winter, other smart devices could be linked to automatically adjust the heating of the air conditioner, for example.

[0624] In this way, by managing just a small amount of information on a user's daily basis, an efficient and effective cleaning process can be implemented, maintaining comfort within the home.

[0625] The following describes the processing flow.

[0626] Step 1:

[0627] The user uses the device to input personal data such as their daily habits, the layout of their home, and the arrangement of their furniture. The device then prepares to send this information to the server.

[0628] Step 2:

[0629] The server receives user data sent from the terminal. The server analyzes this data and uses it as basic data to identify the user's lifestyle patterns and characteristics of their living environment.

[0630] Step 3:

[0631] The server generates an optimal cleaning plan based on the analyzed data. This plan includes cleaning time, cleaning routes, cleaning frequency, and areas to focus on. It utilizes AI generation technology to create a flexible and adjustable plan.

[0632] Step 4:

[0633] The generated cleaning plan is sent from the server to the robotic vacuum cleaner, which is the cleaning device. The robotic vacuum cleaner prepares to start cleaning based on the plan it received.

[0634] Step 5:

[0635] During cleaning, the robotic vacuum cleaner uses its built-in sensors to detect obstacles and proceeds with cleaning while appropriately avoiding them. It collects real-time data and sends the progress of its operation to the server.

[0636] Step 6:

[0637] The server monitors real-time data received from the robotic vacuum cleaner and dynamically adjusts the cleaning plan if any changes are needed. This includes changing the cleaning path and issuing instructions to pause and resume cleaning.

[0638] Step 7:

[0639] The server analyzes the status data of the cleaning device at regular intervals to determine when filter replacement or parts maintenance is necessary. If necessary, the server sends a notification to the user and advises on the required actions.

[0640] Step 8:

[0641] Users receive notifications from the server via their devices and arrange for maintenance and consumables as needed. This process ensures that the cleaning system is always operated in an optimized state.

[0642] (Example 1)

[0643] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0644] In modern living environments, many users are busy, making regular cleaning difficult. Furthermore, efficient and proper cleaning requires complex scheduling and equipment maintenance. However, many existing systems have limitations in managing these elements comprehensively, placing a heavy burden on users. In this situation, there is a need for a system that enables the creation of efficient cleaning plans that take users' lifestyles into account, as well as proper equipment maintenance.

[0645] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0646] In this invention, the server includes means for users to input lifestyle information and housing environment information using a terminal, means for analyzing the input information and automatically generating an optimal cleaning plan using generation AI technology, and means for transmitting instructions to cleaning equipment via wireless communication based on the generated cleaning plan. This enables the implementation of an efficient and effective cleaning process tailored to the user's lifestyle and optimal maintenance of cleaning equipment.

[0647] "User" refers to the entity that utilizes a service or system, and can refer to an individual or a group of people, including families.

[0648] A "terminal" refers to an electronic device used by a user to input information or operate a device.

[0649] "Lifestyle information" refers to information that compiles a user's daily activity time, behavioral patterns, and related data.

[0650] "Residential environment information" refers to information about the user's residence, such as the physical layout and furniture arrangement.

[0651] A "server" refers to a computer system that has a central function of receiving information from users, performing data analysis, and sending instructions.

[0652] "Generative AI technology" refers to technologies that utilize artificial intelligence to perform data analysis and generate new information.

[0653] A "cleaning plan" refers to a schedule that includes efficient cleaning start times and routes, generated based on user information.

[0654] "Wireless communication" refers to technology that transmits and receives data between electronic devices without using cables.

[0655] "Cleaning equipment" refers to automatically operating devices designed to clean a specific space.

[0656] The system according to this invention is designed to manage the user's life more efficiently and provide a comfortable cleaning environment.

[0657] First, the user launches a dedicated application using their device. This app, called the "Cleaning Management App," is available for both iOS and Android. Through the app, the user inputs information about their daily routine (e.g., leaving for work at 7 AM every morning) and their living environment (e.g., room layout and furniture arrangement). This information is appropriately formatted on the device and sent to the server in JSON format or similar.

[0658] The server uses a generative AI model in the process of analyzing the received data. Generally, "generative AI technology" is used as the core technology. Specifically, deep learning models are used in information analysis and the creation of optimized cleaning plans. This automatically generates cleaning start times and optimal route plans that are tailored to the user's lifestyle.

[0659] The generated cleaning plan is transmitted wirelessly from the server to the cleaning equipment. The Wi-Fi protocol is used for this communication. The cleaning equipment is an autonomously operating robotic vacuum cleaner that uses built-in LIDAR and ultrasonic sensors to understand its surroundings in real time while operating.

[0660] For example, if a user registers that they "leave for work at 7 AM every morning," the server will generate a cleaning plan that starts cleaning at 8 AM, after the user has left home. This process can also be synchronized with smart devices to adjust the environment within the home.

[0661] In this system, the server monitors sensor data during cleaning and adjusts the plan as needed. Furthermore, based on long-term usage data, it supports proper maintenance by notifying the user when it is time to clean the filter or replace parts. This notification is delivered via push notifications and email through the device.

[0662] An example of a prompt message would be, "Generate a cleaning plan based on the user's cleaning habits. Input data: daily arrival at 7:00 AM, room layout information, furniture arrangement information." This is how instructions are given to the AI ​​model for generating cleaning. In this way, a comfortable cleaning process can be achieved with minimal user input.

[0663] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0664] Step 1:

[0665] The user launches the cleaning management app using their device. Through the app's interface, they input lifestyle information (e.g., work start time) and home environment information (e.g., floor plan, furniture arrangement). This input data is formatted in JSON format. The device then sends this data to the server.

[0666] Step 2:

[0667] After receiving data from the user, the server begins the information analysis process. In this process, a generative AI model is used, taking the received JSON data as input to generate an optimal cleaning plan. This data analysis utilizes machine learning algorithms, and the server calculates the optimal cleaning route and timing, taking into account the user's lifestyle patterns and the layout of the house. As a result of this calculation, a cleaning schedule and route information are output.

[0668] Step 3:

[0669] The generated cleaning plan is transmitted from the server to the cleaning equipment via wireless communication. The communication protocol used here is Wi-Fi. The transmitted data includes the cleaning start time, route information, and various settings. The cleaning equipment prepares to start operating based on the received plan.

[0670] Step 4:

[0671] Once cleaning begins, the cleaning equipment uses built-in LIDAR and ultrasonic sensors to scan its surroundings. This allows it to perform real-time mapping of the room and autonomously avoid obstacles. The cleaning equipment also transmits progress data, battery status, and other information to a server.

[0672] Step 5:

[0673] During and after cleaning, the server monitors sensor data and progress transmitted from the cleaning equipment. It also has the ability to dynamically adjust the cleaning plan as needed. For example, if the battery level is low, the server sends an instruction to the cleaning equipment to return to the charging station. As a result of this adjustment process, cleaning is performed in real time, adapted to the environmental conditions.

[0674] Step 6:

[0675] After the overall cleaning is complete, the server analyzes long-term usage data of the cleaning equipment. This identifies when filters need cleaning and when parts need replacing, and the server notifies the user of this information. Notifications are sent via push notifications on the device or by email, enabling the user to perform appropriate maintenance.

[0676] (Application Example 1)

[0677] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0678] Modern factories are required to maximize production efficiency. However, the complex layout of production lines and machinery presents challenges in developing and implementing efficient cleaning plans. Furthermore, managing the maintenance and upkeep of cleaning equipment to ensure optimal performance over the long term presents challenges. To address these challenges, an automated and efficient cleaning system is necessary.

[0679] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0680] In this invention, the server includes means for acquiring information about the user's life or work, means for analyzing the acquired information and automatically generating an optimal work plan, and means for transmitting instructions to an automated device based on the generated work plan. This enables efficient cleaning work while optimizing productivity within the factory.

[0681] "Information about the user's life or work" refers to detailed data related to the user's lifestyle and work, particularly daily activities and schedules in factories and homes.

[0682] "Means for automatically generating optimal work plans" refers to a function that automatically creates a plan for efficient and effective work based on collected information, using artificial intelligence or algorithms.

[0683] "Means of transmitting instructions to automated devices" refers to communication methods that convey specific work instructions to machines such as robotic vacuum cleaners and robots based on the generated plan.

[0684] "Real-time data" refers to the latest status information provided during operation, meaning data that allows for immediate understanding of equipment status and environmental changes.

[0685] "Means of notifying users of the need for maintenance" refers to a function that determines when machine parts are deteriorating or when maintenance is needed, and informs users of the appropriate time for repair or replacement.

[0686] "Factory layout information and machine operation schedule" refers collectively to information regarding the internal layout of the factory and schedule information indicating when and how the machines are operating.

[0687] To realize this invention, it is necessary to build an AI-powered automated cleaning system that supports efficient cleaning of factories. This system consists of a management terminal, a server, and an automated cleaning device.

[0688] First, users use a management terminal to input factory layout, machine operating schedules, and other relevant data. This data is then transmitted to the server via wireless or wired connection.

[0689] The server uses a generative AI model to analyze the received information. Specifically, it automatically generates an optimal work plan based on the input information and sets efficient cleaning routes and timings using AI technology. This plan is sent to the automated cleaning equipment via the MQTT protocol.

[0690] The cleaning system uses built-in sensors to monitor the factory environment in real time, enabling efficient cleaning. Data acquired from the sensors is fed back to a server using real-time data processing technologies such as Apache Kafka. The server uses this information to modify the cleaning plan and adjust the system's operating status as needed.

[0691] Furthermore, the server monitors the performance of automated equipment over the long term, predicting, for example, when filters need cleaning or parts need replacing, and appropriately notifying users of the need for maintenance.

[0692] For example, if a factory operates 24 hours a day, the server can track downtime in the production line and generate efficient cleaning routes for those periods. An example of a prompt to input into the AI ​​model is: "Based on the factory layout, production machine placement, and operating schedule, please suggest the optimal cleaning route and start time." This makes it possible to maintain productivity and cleanliness within the factory.

[0693] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0694] Step 1:

[0695] Users use a management terminal to input the factory layout and machine operating schedules. This generates the basic data necessary for the work. The entered information is then sent from the terminal to the server.

[0696] Step 2:

[0697] The server begins analysis using a generating AI model based on the received information. Specifically, it analyzes and optimizes the given data to generate efficient cleaning routes and cleaning times within the factory. This results in the output of an optimal work plan.

[0698] Step 3:

[0699] The generated work plan is sent from the server to the automated cleaning device via the MQTT protocol. The cleaning device then starts work according to this plan at pre-set times.

[0700] Step 4:

[0701] While the cleaning equipment is working, it collects data in real time using its onboard sensors. The server receives this data via Apache Kafka and monitors the equipment's operating status and the surrounding environment. This enables real-time situational awareness.

[0702] Step 5:

[0703] The server modifies the cleaning plan as needed based on the monitoring results. For example, it outputs newly optimized instructions based on the detection of obstacles or the degree of cleaning completion, and sends them back to the cleaning equipment.

[0704] Step 6:

[0705] The server analyzes a series of operational records, including past data, to predict when filters need cleaning and when parts need replacing. Based on this, it notifies the user if maintenance is required. This ensures the long-term efficiency of the cleaning equipment.

[0706] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0707] The present invention is an AI-powered cleaning robot system that recognizes user emotions and incorporates them into the cleaning process to provide a more personalized cleaning experience. Embodiments thereof are described below.

[0708] First, the user accesses the application using their device and inputs information about their lifestyle, the layout of their home, and the arrangement of their furniture. In addition, the device uses its camera and voice input to record the user's facial expressions and tone of voice so that the emotion engine can understand the user's daily emotional state. This information is then sent from the device to the server.

[0709] The server analyzes the received user data and emotional information, and automatically generates the optimal cleaning plan according to the user's current mood. For example, if the user wants to relax, the robot vacuum cleaner's operating noise can be reduced and switched to a quiet mode. Conversely, if the user is in an energetic mood, the cleaning speed can be increased and the settings adjusted to efficiently and quickly clean the entire room.

[0710] The cleaning plan generated in this way is sent from the server to the robotic vacuum cleaner. The robotic vacuum cleaner starts cleaning according to the plan and feeds back the collected data to the server in real time. Based on this data, the server further fine-tunes the plan and flexibly responds to changes in the user's emotions.

[0711] Furthermore, the server can coordinate with other home appliances to create an appropriate home environment during cleaning. For example, if the emotion engine determines that the user is feeling down, it can slightly brighten the lighting and adjust it to a warmer color tone. This makes the entire home a more comfortable space and allows the system to better support the user's emotions.

[0712] For example, if the emotion engine identifies that a user is experiencing stress, the server will adjust the scheduled cleaning time to select a time when the user can relax. This can involve various actions, such as playing relaxation music or activating an aroma diffuser.

[0713] As described above, the present invention enables a cleaning experience linked to the user's emotions, thereby providing a better living environment.

[0714] The following describes the processing flow.

[0715] Step 1:

[0716] The user uses a device to input information about their lifestyle, living arrangements, and furniture placement. The device uses a camera and microphone for the emotion engine to collect emotional information from the user's facial expressions and voice characteristics. All of this data is sent to a server.

[0717] Step 2:

[0718] The server analyzes the data it receives. It uses lifestyle and housing information to understand the user's typical activity patterns, and analyzes emotional information to identify the user's current emotional state.

[0719] Step 3:

[0720] The server generates an optimal cleaning plan based on the analysis results. This includes setting cleaning modes, times, and routes that take the user's feelings into consideration. For example, if it is determined that the user wants to relax, it will select a cleaning setting that operates quietly.

[0721] Step 4:

[0722] The generated cleaning plan is sent from the server to the robotic vacuum cleaner. The vacuum cleaner starts and executes the cleaning according to the received plan. The noise level and speed during cleaning are maintained to match the user's pre-set emotional state.

[0723] Step 5:

[0724] While cleaning is in progress, the robotic vacuum cleaner sends real-time information about its operating status and obstacles to a server. The server evaluates this real-time data and adjusts the cleaning plan as needed.

[0725] Step 6:

[0726] The server further integrates with other smart home appliances to create a home environment that suits the user's emotions. For example, if it determines that the user is feeling down, it will adjust the room lighting to a comfortable level and play calming music to soothe the user.

[0727] Step 7:

[0728] After cleaning is complete, the server checks the status of the cleaning device and determines whether maintenance is required. If necessary, the server sends a notification to the user via the terminal to prompt appropriate action.

[0729] Step 8:

[0730] Users can check notifications from the server via their terminals and perform maintenance on cleaning equipment or adjust environmental settings as needed. This entire process allows users to maintain a comfortable and efficient living environment at all times.

[0731] (Example 2)

[0732] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0733] Traditional cleaning systems often implemented uniform cleaning plans without considering users' feelings or lifestyles. This made it difficult to provide an environment that was sensitive to users' needs, resulting in the challenge of not being able to maintain a completely comfortable space for them.

[0734] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0735] In this invention, the server includes means for inputting user lifestyle information and living space information, means for generating an optimal cleaning plan by analyzing the user's emotional data, and means for transmitting instructions to cleaning equipment using a generated AI model. This makes it possible to provide personalized cleaning that is tailored to the user's emotions and a comfortable home environment.

[0736] "User lifestyle information" refers to data related to daily activities and specific situations, including information about the user's regular actions and habits.

[0737] "Living space information" refers to information about the physical environment within a house, such as infrastructure, floor plan, and furniture arrangement.

[0738] "Emotional data" refers to data that quantifies a user's mental state, mood, and emotional tendencies, and is information analyzed from facial expressions and tone of voice.

[0739] A "cleaning plan" refers to a set of instructions that include specific schedules, routes, and modes of cleaning for living spaces.

[0740] A "generative AI model" is a type of intelligent system that uses machine learning to analyze data and generate new insights and action plans.

[0741] "Cleaning equipment" refers to mechanical devices designed to perform cleaning tasks automatically and efficiently, and is usually in the form of robots.

[0742] "Household appliances" refers to various electrical appliances and equipment used in the home, including lighting, sound systems, and air conditioning equipment.

[0743] "Household environment conditions" refers to the state of physical or sensory environmental conditions within the home, including the adjustment of temperature, sound, and light.

[0744] This invention is a system that provides an advanced cleaning experience that reflects the user's emotional information, and is implemented using the following technical means.

[0745] Users first access a dedicated application via their device and input personal information and living space details. This information is entered using forms on the device, ensuring privacy while collecting highly accurate data. The devices used in this system include smartphones and tablets.

[0746] Furthermore, the device is equipped with a camera and microphone to collect user emotional data. The camera uses facial expression analysis software to analyze the user's facial expressions in real time, and the microphone performs voice data analysis. As a result, the emotional state is quantified and transmitted to a server.

[0747] The server uses a generative AI model to create a cleaning plan based on the received data. The AI ​​model features advanced algorithms that generate an optimized cleaning plan based on the user's emotions and lifestyle information, specifically including switching cleaning modes and setting schedules. This cleaning plan is then transmitted wirelessly to the cleaning device, which in this case refers to a robotic vacuum cleaner.

[0748] Furthermore, the server can interact with other home devices, optimizing the home environment to match the user's mood. This integration enables control of lighting and sound systems, providing a comfortable environment tailored to the user.

[0749] For example, if a user is feeling stressed, the server can select and play relaxing music from a playlist and adjust the lighting to a softer setting. This provides a comprehensive level of comfort that goes beyond mere cleaning, including relaxation.

[0750] An example of a prompt to input into the generating AI model might be, "Create instructions on how the cleaning robot should behave when the user wants to relax."

[0751] This invention aims to provide a better living space by enabling cleaning and environmental optimization tailored to the individual emotional state of the user.

[0752] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0753] Step 1:

[0754] Users access the application using their devices and input lifestyle and living space information. This input data, including information about the user's lifestyle and furniture arrangement, is used as foundational data in subsequent processes. Specifically, users provide data through an input form and save it to their devices by pressing the submit button.

[0755] Step 2:

[0756] The device uses a camera and microphone to collect user emotion data. This includes facial expression analysis and voice tone recording. Input is the user's real-time facial expressions and voice tone, and output is stored in a database as analyzed emotional states. Image recognition software and voice analysis algorithms are used for the analysis.

[0757] Step 3:

[0758] The device transmits collected lifestyle information and emotional data to the server. The input consists of various data stored on the device, while the output is encrypted transmission data using a security protocol. This allows the server to receive the data securely.

[0759] Step 4:

[0760] The server analyzes the received data and creates a cleaning plan using a generative AI model. The input consists of lifestyle information and emotional data, and the output is an optimized cleaning plan tailored to the user's situation. This plan includes the timing of cleaning commencement and the operating mode. Advanced machine learning algorithms are used for data analysis.

[0761] Step 5:

[0762] The server transmits the generated cleaning plan to the robotic cleaning device via wireless communication. The input is specific instructions based on the cleaning plan, and the output is command data for the cleaning device. This causes the cleaning device to begin operating according to the predetermined plan.

[0763] Step 6:

[0764] The robotic cleaning equipment performs cleaning according to the instructions it receives and feeds back the data collected during the operation to the server. The input is sensor information acquired during cleaning, and the output is real-time data sent to the server. The server dynamically adjusts the cleaning plan based on this data.

[0765] Step 7:

[0766] The server works in conjunction with other household appliances to configure the environment in accordance with the user's emotions. Inputs are environmental parameters to be adjusted (such as lighting brightness and music selection), and outputs are control instructions to the appliances. This optimizes not only the cleaning process but the entire home environment to be sensitive to the user's emotions.

[0767] (Application Example 2)

[0768] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0769] Current cleaning systems operate uniformly without considering the user's emotional state, making it difficult to provide an optimal environment for the user. Furthermore, there is a growing demand for environmental improvements in stores and other spaces that are sensitive to the emotions of visitors. However, current technology does not adequately provide efficient means to achieve this.

[0770] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0771] In this invention, the server includes means for analyzing the user's emotional state and dynamically adjusting the cleaning plan based on that information, means for automatically adjusting the store or space environment settings based on the analyzed user's emotional state, and means for recording the user's facial expressions and tone of voice using a camera and a voice input device. This makes it possible to perform cleaning and environmental adjustments in accordance with the user's emotions.

[0772] "User emotional state" refers to the emotional state of a user, analyzed from their facial expressions, tone of voice, and other factors.

[0773] A "cleaning plan" refers to a set of cleaning procedures and schedules optimized based on the user's emotional state and lifestyle.

[0774] "Environment settings" refers to the state of the surrounding environment, including music, lighting, and other spatial elements.

[0775] "Dynamic adjustment" refers to changing settings and plans in real time according to the situation and conditions.

[0776] "Camera and audio input device" refers to photographic and audio recording equipment used to acquire information on the user's facial expressions and voice.

[0777] A "cloud server" refers to a computer system that stores, calculates, and analyzes data remotely via the internet.

[0778] "Feedback" refers to the process of sending back and analyzing data based on the results and state of the actions performed.

[0779] The system of this invention consists of a user, a server, and a terminal. The user collects their facial expressions and voice using a camera and voice input device mounted on a smartphone or smart glasses. These devices transmit the collected data to a cloud server in real time.

[0780] The server analyzes the user's emotional state based on the received data using a generative AI model. It utilizes machine learning frameworks such as TensorFlow for emotion recognition. As a result, it automatically generates an optimal cleaning plan and environmental settings tailored to the user's emotions. The generated plan and settings are then transmitted to the cleaning device and other related appliances for execution.

[0781] For example, if the system determines that the user is relaxed, the server instructs the robot vacuum cleaner to clean in silent mode, simultaneously changes the store lighting to a warm color, and plays calming background music. After the environment is set up, each device feeds its results back to the server, and readjusts are made as needed.

[0782] An example of a prompt message is: "Use a generative AI model to analyze the emotions of customers in the store and suggest the optimal cleaning mode and environmental settings. For example, when customers are relaxing, adjust the music to jazz and the lighting to warm colors."

[0783] This allows for optimal cleaning and environmental adjustments tailored to the user's emotions, providing a more comfortable space.

[0784] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0785] Step 1:

[0786] Users acquire facial and voice information using cameras and voice input devices built into their smartphones or smart glasses. The input consists of facial image data and voice data, which are then used by a generative AI model to analyze emotional states. The data is transmitted to the server in real time.

[0787] Step 2:

[0788] The server processes the received data and uses a facial recognition model and a voice analysis model to analyze the user's emotions. Input is image and audio data from the camera, and output is the user's emotional state (e.g., relaxed, stressed, active, etc.). A machine learning framework (e.g., TensorFlow) is used for the analysis.

[0789] Step 3:

[0790] The server generates a cleaning plan optimized for the user's emotions based on the analyzed emotional state. The input is the analyzed emotional state, and the output is the custom cleaning plan. Specific actions may include instructing the cleaning device to switch to silent mode or high-speed mode.

[0791] Step 4:

[0792] The server sends instructions to relevant home appliances to configure the environment appropriately. The inputs are the analyzed emotional state and associated cleaning plan, and the output is specific appliance operation commands. Examples of specific actions include adjusting the lighting color or playing relaxing music from speakers.

[0793] Step 5:

[0794] The server receives feedback on the results of the instructed cleaning and environmental settings, and uses this information to make further adjustments. Input is feedback information from each device, and output is the updated cleaning plan and environmental settings as needed. Specific examples of its operation include re-evaluating the cleaning area and adjusting the volume.

[0795] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0796] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0797] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0798] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0799] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0800] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0801] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0802] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0803] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0804] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0805] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0806] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0807] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0808] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0809] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0810] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0811] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0812] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0813] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0814] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0815] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0816] The following is further disclosed regarding the embodiments described above.

[0817] (Claim 1)

[0818] A means for inputting user lifestyle information and housing information,

[0819] A means for analyzing the input information and automatically generating an optimal cleaning plan,

[0820] Means for transmitting instructions to a cleaning device based on the generated cleaning plan,

[0821] A means for monitoring real-time data acquired from the cleaning device and adjusting the cleaning plan as needed,

[0822] A means of analyzing the condition of the cleaning device and notifying the user of the need for maintenance,

[0823] A system that includes this.

[0824] (Claim 2)

[0825] The system according to claim 1, comprising means for determining the optimal cleaning start time predicted based on the user's lifestyle.

[0826] (Claim 3)

[0827] The system according to claim 1, comprising means for coordinating with other home appliances to create an optimal home environment while the cleaning device is in operation.

[0828] "Example 1"

[0829] (Claim 1)

[0830] A means by which users can input lifestyle information and housing environment information using a terminal,

[0831] A means for analyzing the input information and automatically generating an optimal cleaning plan using generation AI technology,

[0832] A means for transmitting instructions to cleaning equipment via wireless communication based on the generated cleaning plan,

[0833] A means for monitoring real-time status data and sensor data acquired from cleaning equipment and dynamically adjusting the cleaning plan as needed,

[0834] A means of analyzing long-term usage data of cleaning equipment and notifying users of when parts need to be replaced or when filters need to be cleaned,

[0835] A system that includes this.

[0836] (Claim 2)

[0837] The system according to claim 1, comprising means for predicting and setting the optimal cleaning start time based on the user's registered lifestyle activity information.

[0838] (Claim 3)

[0839] The system according to claim 1, comprising means for optimizing the environment inside a house while the cleaning equipment is in operation, in cooperation with other household electronic devices.

[0840] "Application Example 1"

[0841] (Claim 1)

[0842] Means for obtaining information about the user's life or work,

[0843] A means for analyzing the acquired information and automatically generating an optimal work plan,

[0844] Means for transmitting instructions to an automated device based on the generated work plan,

[0845] A means for monitoring real-time data acquired from the aforementioned automated device and adjusting the work plan as necessary,

[0846] A means of analyzing the status of automated equipment and notifying users of the need for maintenance,

[0847] A means for generating a plan based on the layout information and machine operation schedule within the factory,

[0848] A system that includes this.

[0849] (Claim 2)

[0850] The system according to claim 1, comprising means for determining an optimal work start time predicted based on the user's daily or work schedule.

[0851] (Claim 3)

[0852] The system according to claim 1, comprising means for coordinating with other equipment to create an optimal environment during the operation of the automated device.

[0853] "Example 2 of combining an emotion engine"

[0854] (Claim 1)

[0855] A means for inputting user lifestyle information and living space information,

[0856] A means for automatically generating an optimal cleaning plan by analyzing the input information and user sentiment data,

[0857] A means of sending cleaning instructions to cleaning equipment based on user emotions using a generative AI model,

[0858] A means for monitoring real-time data acquired from the cleaning equipment and adjusting the cleaning plan in response to changes in the user's emotions,

[0859] A means of coordinating with other home devices to adjust the home environment to match the user's emotions,

[0860] A system that includes this.

[0861] (Claim 2)

[0862] The system according to claim 1, comprising means for determining the optimal cleaning start time based on user emotion data.

[0863] (Claim 3)

[0864] The system according to claim 1, comprising means for providing a home environment that is most suitable to the user's emotions while the cleaning device is in operation, in cooperation with other home appliances.

[0865] "Application example 2 of combining emotional engines"

[0866] (Claim 1)

[0867] A means of analyzing the user's emotional state and dynamically adjusting the cleaning plan based on that information,

[0868] A means for automatically adjusting the environmental settings of a store or space based on the analyzed emotional state of the user,

[0869] A means for recording the user's facial expressions and tone of voice using a camera and an audio input device,

[0870] A means for transmitting the recorded information to a cloud server, analyzing the data, and generating optimal environment settings,

[0871] A means for sending instructions to implement an optimized environment and cleaning plan, and for providing feedback on the results of the implementation,

[0872] A system that includes this.

[0873] (Claim 2)

[0874] The system according to claim 1, comprising means for dynamically adjusting music and light source settings to improve the environment in accordance with the user's emotional state.

[0875] (Claim 3)

[0876] The system according to claim 1, comprising means for coordinating with multiple electronic devices to create an optimal store or spatial environment based on the user's emotions. [Explanation of Symbols]

[0877] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for inputting user lifestyle information and housing information, A means for analyzing the input information and automatically generating an optimal cleaning plan, Means for transmitting instructions to a cleaning device based on the generated cleaning plan, A means for monitoring real-time data acquired from the cleaning device and adjusting the cleaning plan as needed, A means of analyzing the condition of the cleaning device and notifying the user of the need for maintenance, A system that includes this.

2. The system according to claim 1, comprising means for determining the optimal cleaning start time predicted based on the user's lifestyle habits.

3. The system according to claim 1, comprising means for coordinating with other home appliances to create an optimal home environment while the cleaning device is in operation.

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